Machine_Learning/Fake News Detection/Model/PridictionModel.ipynb

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        "import pandas as pd\n",
        "import sklearn\n",
        "import itertools\n",
        "import numpy as np\n",
        "import seaborn as sb\n",
        "import re\n",
        "import nltk\n",
        "import pickle\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from matplotlib import pyplot as plt\n",
        "from sklearn.linear_model import PassiveAggressiveClassifier,LogisticRegression\n",
        "from nltk.stem import WordNetLemmatizer\n",
        "from nltk.corpus import stopwords"
      ]
    },
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        "train_df = pd.read_csv('/content/drive/MyDrive/train.csv')"
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En esta ocasi\\u00f3n pretend\\u00edan prenderlo con un mechero antes de lanzarlo al c\\u00e9sped. \\nLas autoridades han vuelto a pedir a los aficionados que dejen de lanzar cosas al campo como botellas, monedas y jugadores del Barcelona. El dispositivo de seguridad no puedo hacer nada por evitar que algunos hinchas introdujeran a jugadores barcelonistas a la grada, pues los llevaban camuflados dentro de bocadillos de gran tama\\u00f1o. \\nEl partido pudo ser reanudado cuando el \\u00e1rbitro apart\\u00f3 a un rinc\\u00f3n del c\\u00e9sped al jugador barcelonista.\",\n          \"Written by Jacob G. Hornberger   As US officials continue to accuse Russia of meddling with the US presidential election, an accusation that they have provided no evidence whatsoever to support, let\\u2019s review some of the US government\\u2019s history of meddling with elections in others countries.1. In 1951, the democratically elected parliament of Iran elected a man named Mohammad Mossadegh to be Iran\\u2019s prime minister. Mossadegh angered British Empire officials by nationalizing British oil interests in the country.British officials then turned to the CIA for assistance. In 1953, the CIA secretly fomented a violent coup in Iran, which succeeded in ousting Mossadegh from power and making the Shah of Iran the supreme unelected dictator of the country.To fortify the Shah\\u2019s dictatorial hold on power, the CIA helped organize and train the his domestic police force, the Savak, which was essentially a combination of the CIA, the NSA, and the military. Part of the CIA\\u2019s training involved teaching Savak agents the art of torture.For the next 26 years, the Iranian people suffered under one of the most brutal and tyrannical dictatorships in the world, one that US officials fully supported and called an ally and friend of the United States.In 1979, Iranians successfully revolted against the Shah\\u2019s regime and ousted him from power. One result was not a restoration of the democratic system that had elected Mossadegh but rather another brutal dictatorship, this time a religious one. Another result is the bad relations between the Iran and US governments that continues to exist today.2. In 1951, the Guatemalan people democratically elected a man named Jacobo Arbenz to be their president. Arbenz, however, was not satisfactory to US officials, especially the national-security branch of the government, specifically the Pentagon and the CIA. The reason that US officials opposed Arbenz was that he was a socialist, and US officials considered a socialist president of Guatemala to be a threat to \\u201cnational security\\u201d here in the United States.In 1954 \\u2014 one year after the coup in Iran, the CIA fomented a violent military coup that succeeded in removing Arbenz from power and replacing him with one of the most brutal unelected military dictators in Latin American history, a man named Carlos Castillo Armas. The CIA had a kill list prepared for the coup, which Arbenz was able to escape by fleeing the country before Castillo was able to get him. The CIA\\u2019s destruction of Guatemala\\u2019s democratic system threw the nation into a 30-year civil war that ended up killing millions of Guatemalan people, especially many of the poor.3. In 1960 a man named Patrice Lamumba was elected Congo\\u2019s first prime minister after independence from Belgium. Lamumba spoke out against Western imperialism and refused to take sides in the Cold War, which caused the CIA to conclude that he was a threat to \\u201cnational security.\\u201d The CIA orchestrated the assassination of Lamumba, which ended up taking place on January 17, 1961, just three days before President Kennedy, who liked Lamumba and who would have ordered the CIA to stand down, was to be sworn into office.4. In 1970 a man named Salvador Allende received a plurality of votes in the presidential election in Chile. Pursuant to the Chilean constitution, the election was thrown into the national congress. President Richard Nixon, his national-security team, the Pentagon, and the CIA concluded that because Allende believed in communism and socialism, he posed a grave threat to \\u201cnational security\\u201d here in the United States. The CIA attempted to bribe members of the congress to vote against Allende. It also orchestrated the kidnapping of the head of Chile\\u2019s armed forces, Gen Rene Schneider, who opposed a US military coup in his country, especially since a coup would violate the country\\u2019s constitution. The kidnapping attempt on Schneider left him dead.The CIA then fomented a coup that took place on 9/11 1973 that violently ousted Allende from power and left him dead. Replacing him was army Gen. Augusto Pinochet, one of the most brutal unelected military dictators in history. By the time Pinochet\\u2019s 17-year reign of military terror came to an end in 1990, he and his CIA-supported goons had incarcerated, raped, tortured, or killed tens of thousands of innocent people \\u2014 that is, people whose only \\u201ccrime\\u201d was believing in socialism \\u2014 with the full support of the CIA, Pentagon, Nixon, and his \\u201cnational security\\u201d team.Of course, there are also the more recent support of regime-change operations that ousted democratically elected presidents that the US government disapproved of, such as in Ukraine and Egypt.And then there is the long list of countries where unelected dictators were targeted for regime change by the US national security state and, where successful, replaced with a brutal unelected pro-US dictator. Cuba, Indonesia, Iraq, Libya, and Syria all come to mind.US officials need to keep in mind that when they point their accusatory index finger at Russia for supposedly meddling in the US presidential election, US officials have, at the same time, three fingers pointing back at themselves. Reprinted with permission from the Future of Freedom Foundation . Related\",\n          \"When hearing of an establishment called the Black and Blue Steakhouse, one could reasonably surmise that some, or at the very least one, extremely tough person could be found somewhere in there. Well, the three terrorists who attacked London Bridge over the weekend found the Black and Blue Steakhouse, and they found the toughest man in the house. [Or, maybe more to the point, he found them.  Roy Larner, 47, is a huge fan of the South East London soccer team Millwall F. C. The team is known as the Lions, and when   terrorists entered the Black and Blue to kill innocent people, Larner let them know who is the true king of the jungle. After the terrorists entered, with obvious bad intentions, Larner sprang into action: \\u201cLike an idiot I shouted back at them. I thought, \\u2018I need to take the p*** out of these b*****s.\\u2019 \\u201cI took a few steps towards them and said, \\u2018F*** you, I\\u2019m Millwall.\\u2019 So they started attacking me. \\u201cI stood in front of them trying to fight them off. Everyone else ran to the back. I was on my own against all three of them, that\\u2019s why I got hurt so much. It was just me, trying to grab them with my bare hands and hold on. I was swinging. \\u201cI got stabbed and sliced eight times. They got me in my head, chest and both hands. There was blood everywhere. \\u201cThey were saying, \\u2018Islam, Islam!\\u2019 I said again, \\u2018F*** you, I\\u2019m Millwall!\\u2019 \\u201cIt was the worst thing I could have done as they carried on attacking me. \\u201cLuckily, none of the blows were straight at me or I\\u2019d be dead. \\u201d A petition has begun, with the aim of awarding Larner with the George Cross for bravery. The award is the second highest commendation granted by Great Britain. Looking at his scars, it\\u2019s really hard to imagine that he won\\u2019t get it. If Millwall is looking for a new slogan, they may have found it. \\u201cF*** you, I\\u2019m Millwall!\\u201d has a nice ring to it. Follow Dylan Gwinn on Twitter: @themightygwinn\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"label\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2a3e11c4-95d0-43ef-8a1d-0388e1d94b6a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "    id                                              title  \\\n",
              "0    0  House Dem Aide: We Didn’t Even See Comey’s Let...   \n",
              "1    1  FLYNN: Hillary Clinton, Big Woman on Campus - ...   \n",
              "2    2                  Why the Truth Might Get You Fired   \n",
              "3    3  15 Civilians Killed In Single US Airstrike Hav...   \n",
              "4    4  Iranian woman jailed for fictional unpublished...   \n",
              "5    5  Jackie Mason: Hollywood Would Love Trump if He...   \n",
              "6    6  Life: Life Of Luxury: Elton John’s 6 Favorite ...   \n",
              "7    7  Benoît Hamon Wins French Socialist Party’s Pre...   \n",
              "8    8  Excerpts From a Draft Script for Donald Trump’...   \n",
              "9    9  A Back-Channel Plan for Ukraine and Russia, Co...   \n",
              "10  10  Obama’s Organizing for Action Partners with So...   \n",
              "11  11  BBC Comedy Sketch \"Real Housewives of ISIS\" Ca...   \n",
              "12  12  Russian Researchers Discover Secret Nazi Milit...   \n",
              "13  13  US Officials See No Link Between Trump and Russia   \n",
              "14  14  Re: Yes, There Are Paid Government Trolls On S...   \n",
              "\n",
              "                          author  \\\n",
              "0                  Darrell Lucus   \n",
              "1                Daniel J. Flynn   \n",
              "2             Consortiumnews.com   \n",
              "3                Jessica Purkiss   \n",
              "4                 Howard Portnoy   \n",
              "5                Daniel Nussbaum   \n",
              "6                            NaN   \n",
              "7                Alissa J. Rubin   \n",
              "8                            NaN   \n",
              "9   Megan Twohey and Scott Shane   \n",
              "10                   Aaron Klein   \n",
              "11               Chris Tomlinson   \n",
              "12                 Amando Flavio   \n",
              "13                    Jason Ditz   \n",
              "14                  AnotherAnnie   \n",
              "\n",
              "                                                 text  label  \n",
              "0   House Dem Aide: We Didn’t Even See Comey’s Let...      1  \n",
              "1   Ever get the feeling your life circles the rou...      0  \n",
              "2   Why the Truth Might Get You Fired October 29, ...      1  \n",
              "3   Videos 15 Civilians Killed In Single US Airstr...      1  \n",
              "4   Print \\nAn Iranian woman has been sentenced to...      1  \n",
              "5   In these trying times, Jackie Mason is the Voi...      0  \n",
              "6   Ever wonder how Britain’s most iconic pop pian...      1  \n",
              "7   PARIS  —   France chose an idealistic, traditi...      0  \n",
              "8   Donald J. Trump is scheduled to make a highly ...      0  \n",
              "9   A week before Michael T. Flynn resigned as nat...      0  \n",
              "10  Organizing for Action, the activist group that...      0  \n",
              "11  The BBC produced spoof on the “Real Housewives...      0  \n",
              "12  The mystery surrounding The Third Reich and Na...      1  \n",
              "13  Clinton Campaign Demands FBI Affirm Trump's Ru...      1  \n",
              "14  Yes, There Are Paid Government Trolls On Socia...      1  "
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_df.head(15)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.10674Z",
          "iopub.status.busy": "2021-05-25T06:50:32.106434Z",
          "iopub.status.idle": "2021-05-25T06:50:32.120541Z",
          "shell.execute_reply": "2021-05-25T06:50:32.119386Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.106712Z"
        },
        "id": "tcLAi-N-VOh-",
        "outputId": "e96ae326-19ef-402a-84fe-456a61bb2378"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(20800, 5)"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_df.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.124489Z",
          "iopub.status.busy": "2021-05-25T06:50:32.12414Z",
          "iopub.status.idle": "2021-05-25T06:50:32.140229Z",
          "shell.execute_reply": "2021-05-25T06:50:32.139288Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.124461Z"
        },
        "id": "TpnxrMIlVOh-",
        "outputId": "e122d6c4-d34a-4783-a4a1-50eefedd9b59"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 20800 entries, 0 to 20799\n",
            "Data columns (total 5 columns):\n",
            " #   Column  Non-Null Count  Dtype \n",
            "---  ------  --------------  ----- \n",
            " 0   id      20800 non-null  int64 \n",
            " 1   title   20242 non-null  object\n",
            " 2   author  18843 non-null  object\n",
            " 3   text    20761 non-null  object\n",
            " 4   label   20800 non-null  int64 \n",
            "dtypes: int64(2), object(3)\n",
            "memory usage: 812.6+ KB\n"
          ]
        }
      ],
      "source": [
        "train_df.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s9cYLl9wVOh-",
        "outputId": "87dbacf5-d1d3-428d-b0e4-32de6690d0e8"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([10413, 10387])"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# def create_distribution(dataFile):\n",
        "#     return sb.countplot(x='label', data=dataFile, palette='hls')\n",
        "\n",
        "# #by calling below we can see that training, test and valid data seems to be failry evenly distributed between the classes\n",
        "# create_distribution(train_df)\n",
        "train_df['label'].value_counts().values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "bjbwisJ8VOh_",
        "outputId": "1037a327-e880-497d-8d5b-f0e34efacf1e"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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t09133y1JKi8vV0VFhRISEuznuFwu9evXT4WFhZKkwsJCRUZG2oEjSQkJCQoODlZRUZE95o477lBoaKg9JjExUWVlZfrqq6/qnVt1dbV8Pp/fAgAAzBTwOzlTpkyRz+dTly5d1KxZM509e1bPPfeckpOTJUkVFRWSJLfb7fc8t9ttb6uoqFC7du38JxoSoqioKL8xsbGx5+2jblurVq3Om1tmZqaeeeaZAJwlAAC40gX8Ts6KFSuUl5enZcuW6cMPP1Rubq5efvll5ebmBvpQP9jUqVPl9Xrt5fDhw409JQAA0EACfidn0qRJmjJlikaMGCFJ6tGjh/7yl78oMzNTo0aNksfjkSRVVlaqffv29vMqKyvVq1cvSZLH49HRo0f99nvmzBkdO3bMfr7H41FlZaXfmLrHdWO+y+FwyOFwXPpJAgCAK17A7+R8/fXXCg72322zZs1UW1srSYqNjZXH49GmTZvs7T6fT0VFRYqPj5ckxcfHq6qqSsXFxfaYzZs3q7a2Vv369bPHbN26VadPn7bHFBQU6MYbb6z3pSoAAHB1CXjk3HfffXruueeUn5+vgwcPatWqVZozZ47uv/9+SVJQUJDS09M1a9YsrVmzRnv27NHIkSMVHR2tYcOGSZK6du2qIUOGaMyYMdqxY4fef/99paWlacSIEYqOjpYkPfLIIwoNDVVKSopKS0u1fPlyzZ8/XxMnTgz0KQEAgCYo4C9XLViwQNOnT9cvfvELHT16VNHR0fr5z3+ujIwMe8zkyZN18uRJjR07VlVVVbr99tu1fv16hYWF2WPy8vKUlpamQYMGKTg4WMOHD1d2dra93eVyaePGjUpNTVXfvn3Vpk0bZWRk8PFxAAAgSQqyzv0q4quMz+eTy+WS1+uV0+kM6L47T8kP6P4A0xx8IamxpxAQXOvAhTXUdX6xP7/53VUAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIzVI5Pzv//6vHn30UbVu3Vrh4eHq0aOHdu3aZW+3LEsZGRlq3769wsPDlZCQoP379/vt49ixY0pOTpbT6VRkZKRSUlJ04sQJvzG7d+/WgAEDFBYWppiYGGVlZTXE6QAAgCYo4JHz1Vdf6bbbblPz5s21bt06ffrpp5o9e7ZatWplj8nKylJ2drZycnJUVFSkiIgIJSYm6tSpU/aY5ORklZaWqqCgQGvXrtXWrVs1duxYe7vP59PgwYPVqVMnFRcX66WXXtKMGTO0ePHiQJ8SAABogkICvcMXX3xRMTExWrJkib0uNjbW/rNlWZo3b56mTZumoUOHSpLeeOMNud1urV69WiNGjNDevXu1fv167dy5U3FxcZKkBQsW6J577tHLL7+s6Oho5eXlqaamRq+//rpCQ0N10003qaSkRHPmzPGLIQAAcHUK+J2cNWvWKC4uTg899JDatWun3r1767e//a29vby8XBUVFUpISLDXuVwu9evXT4WFhZKkwsJCRUZG2oEjSQkJCQoODlZRUZE95o477lBoaKg9JjExUWVlZfrqq6/qnVt1dbV8Pp/fAgAAzBTwyPnzn/+sRYsW6frrr9eGDRv0xBNPaPz48crNzZUkVVRUSJLcbrff89xut72toqJC7dq189seEhKiqKgovzH17ePcY3xXZmamXC6XvcTExFzi2QIAgCtVwCOntrZWffr00fPPP6/evXtr7NixGjNmjHJycgJ9qB9s6tSp8nq99nL48OHGnhIAAGggAY+c9u3bq1u3bn7runbtqkOHDkmSPB6PJKmystJvTGVlpb3N4/Ho6NGjftvPnDmjY8eO+Y2pbx/nHuO7HA6HnE6n3wIAAMwU8Mi57bbbVFZW5rfus88+U6dOnSR9+yZkj8ejTZs22dt9Pp+KiooUHx8vSYqPj1dVVZWKi4vtMZs3b1Ztba369etnj9m6datOnz5tjykoKNCNN97o90kuAABwdQp45EyYMEEffPCBnn/+eR04cEDLli3T4sWLlZqaKkkKCgpSenq6Zs2apTVr1mjPnj0aOXKkoqOjNWzYMEnf3vkZMmSIxowZox07duj9999XWlqaRowYoejoaEnSI488otDQUKWkpKi0tFTLly/X/PnzNXHixECfEgAAaIIC/hHyW265RatWrdLUqVM1c+ZMxcbGat68eUpOTrbHTJ48WSdPntTYsWNVVVWl22+/XevXr1dYWJg9Ji8vT2lpaRo0aJCCg4M1fPhwZWdn29tdLpc2btyo1NRU9e3bV23atFFGRgYfHwcAAJKkIMuyrMaeRGPx+XxyuVzyer0Bf39O5yn5Ad0fYJqDLyQ19hQCgmsduLCGus4v9uc3v7sKAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGKnBI+eFF15QUFCQ0tPT7XWnTp1SamqqWrdurWuuuUbDhw9XZWWl3/MOHTqkpKQktWjRQu3atdOkSZN05swZvzHvvfee+vTpI4fDoeuuu05Lly5t6NMBAABNRINGzs6dO/Wb3/xGN998s9/6CRMm6A9/+INWrlypLVu26MiRI3rggQfs7WfPnlVSUpJqamq0fft25ebmaunSpcrIyLDHlJeXKykpSQMHDlRJSYnS09P1+OOPa8OGDQ15SgAAoIlosMg5ceKEkpOT9dvf/latWrWy13u9Xr322muaM2eO7rrrLvXt21dLlizR9u3b9cEHH0iSNm7cqE8//VS///3v1atXL91999169tlntXDhQtXU1EiScnJyFBsbq9mzZ6tr165KS0vTgw8+qLlz5zbUKQEAgCakwSInNTVVSUlJSkhI8FtfXFys06dP+63v0qWLOnbsqMLCQklSYWGhevToIbfbbY9JTEyUz+dTaWmpPea7+05MTLT3UZ/q6mr5fD6/BQAAmCmkIXb69ttv68MPP9TOnTvP21ZRUaHQ0FBFRkb6rXe73aqoqLDHnBs4ddvrtn3fGJ/Pp2+++Ubh4eHnHTszM1PPPPPMP3xeAACg6Qj4nZzDhw/rV7/6lfLy8hQWFhbo3V+SqVOnyuv12svhw4cbe0oAAKCBBDxyiouLdfToUfXp00chISEKCQnRli1blJ2drZCQELndbtXU1KiqqsrveZWVlfJ4PJIkj8dz3qet6h7/vTFOp7PeuziS5HA45HQ6/RYAAGCmgEfOoEGDtGfPHpWUlNhLXFyckpOT7T83b95cmzZtsp9TVlamQ4cOKT4+XpIUHx+vPXv26OjRo/aYgoICOZ1OdevWzR5z7j7qxtTtAwAAXN0C/p6cli1bqnv37n7rIiIi1Lp1a3t9SkqKJk6cqKioKDmdTv3yl79UfHy8+vfvL0kaPHiwunXrpscee0xZWVmqqKjQtGnTlJqaKofDIUkaN26cXnnlFU2ePFk/+9nPtHnzZq1YsUL5+fmBPiUAANAENcgbj/+euXPnKjg4WMOHD1d1dbUSExP16quv2tubNWumtWvX6oknnlB8fLwiIiI0atQozZw50x4TGxur/Px8TZgwQfPnz1eHDh30u9/9TomJiY1xSgAA4AoTZFmW1diTaCw+n08ul0terzfg78/pPIU7SsD3OfhCUmNPISC41oELa6jr/GJ/fvO7qwAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGInIAAICRiBwAAGAkIgcAABiJyAEAAEYicgAAgJGIHAAAYCQiBwAAGInIAQAARiJyAACAkYgcAABgJCIHAAAYicgBAABGCnjkZGZm6pZbblHLli3Vrl07DRs2TGVlZX5jTp06pdTUVLVu3VrXXHONhg8frsrKSr8xhw4dUlJSklq0aKF27dpp0qRJOnPmjN+Y9957T3369JHD4dB1112npUuXBvp0AABAExXwyNmyZYtSU1P1wQcfqKCgQKdPn9bgwYN18uRJe8yECRP0hz/8QStXrtSWLVt05MgRPfDAA/b2s2fPKikpSTU1Ndq+fbtyc3O1dOlSZWRk2GPKy8uVlJSkgQMHqqSkROnp6Xr88ce1YcOGQJ8SAABogoIsy7Ia8gBffvml2rVrpy1btuiOO+6Q1+tV27ZttWzZMj344IOSpH379qlr164qLCxU//79tW7dOt177706cuSI3G63JCknJ0dPPvmkvvzyS4WGhurJJ59Ufn6+PvnkE/tYI0aMUFVVldavX39Rc/P5fHK5XPJ6vXI6nQE9785T8gO6P8A0B19IauwpBATXOnBhDXWdX+zP7wZ/T47X65UkRUVFSZKKi4t1+vRpJSQk2GO6dOmijh07qrCwUJJUWFioHj162IEjSYmJifL5fCotLbXHnLuPujF1+wAAAFe3kIbceW1trdLT03Xbbbepe/fukqSKigqFhoYqMjLSb6zb7VZFRYU95tzAqdtet+37xvh8Pn3zzTcKDw8/bz7V1dWqrq62H/t8vks7QQAAcMVq0Ds5qamp+uSTT/T222835GEuWmZmplwul73ExMQ09pQAAEADabDISUtL09q1a/WnP/1JHTp0sNd7PB7V1NSoqqrKb3xlZaU8Ho895ruftqp7/PfGOJ3Oeu/iSNLUqVPl9Xrt5fDhw5d0jgAA4MoV8MixLEtpaWlatWqVNm/erNjYWL/tffv2VfPmzbVp0yZ7XVlZmQ4dOqT4+HhJUnx8vPbs2aOjR4/aYwoKCuR0OtWtWzd7zLn7qBtTt4/6OBwOOZ1OvwUAAJgp4O/JSU1N1bJly/TOO++oZcuW9ntoXC6XwsPD5XK5lJKSookTJyoqKkpOp1O//OUvFR8fr/79+0uSBg8erG7duumxxx5TVlaWKioqNG3aNKWmpsrhcEiSxo0bp1deeUWTJ0/Wz372M23evFkrVqxQfj6fdAAAAA1wJ2fRokXyer360Y9+pPbt29vL8uXL7TFz587Vvffeq+HDh+uOO+6Qx+PRf//3f9vbmzVrprVr16pZs2aKj4/Xo48+qpEjR2rmzJn2mNjYWOXn56ugoEA9e/bU7Nmz9bvf/U6JiYmBPiUAANAENfj35FzJ+J4coPHwPTmA+Yz/nhwAAIDGQOQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAIxE5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjNTkI2fhwoXq3LmzwsLC1K9fP+3YsaOxpwQAAK4ATTpyli9frokTJ+rpp5/Whx9+qJ49eyoxMVFHjx5t7KkBAIBG1qQjZ86cORozZox++tOfqlu3bsrJyVGLFi30+uuvN/bUAABAIwtp7An8o2pqalRcXKypU6fa64KDg5WQkKDCwsJ6n1NdXa3q6mr7sdfrlST5fL6Az6+2+uuA7xMwSUNcd42Bax24sIa6zuv2a1nW945rspHzt7/9TWfPnpXb7fZb73a7tW/fvnqfk5mZqWeeeea89TExMQ0yRwAX5prX2DMA0NAa+jo/fvy4XC7XBbc32cj5R0ydOlUTJ060H9fW1urYsWNq3bq1goKCGnFmaEg+n08xMTE6fPiwnE5nY08HQAPhWr96WJal48ePKzo6+nvHNdnIadOmjZo1a6bKykq/9ZWVlfJ4PPU+x+FwyOFw+K2LjIxsqCniCuN0OvkfH3AV4Fq/OnzfHZw6TfaNx6Ghoerbt682bdpkr6utrdWmTZsUHx/fiDMDAABXgiZ7J0eSJk6cqFGjRikuLk7/8i//onnz5unkyZP66U9/2thTAwAAjaxJR85PfvITffnll8rIyFBFRYV69eql9evXn/dmZFzdHA6Hnn766fNeqgRgFq51fFeQ9fc+fwUAANAENdn35AAAAHwfIgcAABiJyAEAAEYicgAATd7SpUv53jOch8hBkxIUFPS9y4wZMxp7igAuwejRo+u9tg8cONDYU0MT1KQ/Qo6rz1//+lf7z8uXL1dGRobKysrsdddcc439Z8uydPbsWYWE8J850JQMGTJES5Ys8VvXtm3bRpoNmjLu5KBJ8Xg89uJyuRQUFGQ/3rdvn1q2bKl169apb9++cjgc2rZtm0aPHq1hw4b57Sc9PV0/+tGP7Me1tbXKzMxUbGyswsPD1bNnT/3nf/7n5T05AJK+/b6bc691j8ej+fPnq0ePHoqIiFBMTIx+8Ytf6MSJExfcx8cff6yBAweqZcuWcjqd6tu3r3bt2mVv37ZtmwYMGKDw8HDFxMRo/PjxOnny5OU4PVxGRA6MM2XKFL3wwgvau3evbr755ot6TmZmpt544w3l5OSotLRUEyZM0KOPPqotW7Y08GwBXIzg4GBlZ2ertLRUubm52rx5syZPnnzB8cnJyerQoYN27typ4uJiTZkyRc2bN5ckff755xoyZIiGDx+u3bt3a/ny5dq2bZvS0tIu1+ngMuE+Powzc+ZM/eu//utFj6+urtbzzz+vP/7xj/bvPfvnf/5nbdu2Tb/5zW905513NtRUAdRj7dq1fi8933333Vq5cqX9uHPnzpo1a5bGjRunV199td59HDp0SJMmTVKXLl0kSddff729LTMzU8nJyUpPT7e3ZWdn684779SiRYsUFhbWAGeFxkDkwDhxcXE/aPyBAwf09ddfnxdGNTU16t27dyCnBuAiDBw4UIsWLbIfR0RE6I9//KMyMzO1b98++Xw+nTlzRqdOndLXX3+tFi1anLePiRMn6vHHH9ebb76phIQEPfTQQ7r22mslfftS1u7du5WXl2ePtyxLtbW1Ki8vV9euXRv+JHFZEDkwTkREhN/j4OBgffe3l5w+fdr+c93r+vn5+fqnf/onv3H8Dhzg8ouIiNB1111nPz548KDuvfdePfHEE3ruuecUFRWlbdu2KSUlRTU1NfVGzowZM/TII48oPz9f69at09NPP623335b999/v06cOKGf//znGj9+/HnP69ixY4OeGy4vIgfGa9u2rT755BO/dSUlJfbr8926dZPD4dChQ4d4aQq4AhUXF6u2tlazZ89WcPC3byVdsWLF333eDTfcoBtuuEETJkzQww8/rCVLluj+++9Xnz599Omnn/qFFMzEG49hvLvuuku7du3SG2+8of379+vpp5/2i56WLVvq17/+tSZMmKDc3Fx9/vnn+vDDD7VgwQLl5uY24swBSNJ1112n06dPa8GCBfrzn/+sN998Uzk5ORcc/8033ygtLU3vvfee/vKXv+j999/Xzp077ZehnnzySW3fvl1paWkqKSnR/v379c477/DGYwMROTBeYmKipk+frsmTJ+uWW27R8ePHNXLkSL8xzz77rKZPn67MzEx17dpVQ4YMUX5+vmJjYxtp1gDq9OzZU3PmzNGLL76o7t27Ky8vT5mZmRcc36xZM/3f//2fRo4cqRtuuEH/9m//prvvvlvPPPOMJOnmm2/Wli1b9Nlnn2nAgAHq3bu3MjIyFB0dfblOCZdJkPXdNysAAAAYgDs5AADASEQOAAAwEpEDAACMROQAAAAjETkAAMBIRA4AADASkQMAAIxE5AAAACMROQAAwEhEDgAAMBKRAwAAjETkAAAAI/0/hC2U4Tvr+v0AAAAASUVORK5CYII=",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "bars= plt.bar(['True','False'],train_df['label'].value_counts().values)\n",
        "for bar in bars:\n",
        "    yval = bar.get_height()\n",
        "    plt.text(bar.get_x() + bar.get_width() / 2, yval, round(yval, 2), ha='center', va='bottom')\n",
        "\n",
        "plt.show()\n",
        "#Hence data has nearly equal cases of True and False News."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.306146Z",
          "iopub.status.busy": "2021-05-25T06:50:32.305826Z",
          "iopub.status.idle": "2021-05-25T06:50:32.335357Z",
          "shell.execute_reply": "2021-05-25T06:50:32.33417Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.306118Z"
        },
        "id": "n5YaMAAKVOh_",
        "outputId": "1d325f85-3dbb-4f6e-d2a5-5b6e02517bf4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[1mCOLUMN\u001b[0m                        \u001b[1mNULL VALUES COUNT\u001b[0m\n",
            "id                                0\n",
            "title                             558\n",
            "author                            1957\n",
            "text                              39\n",
            "label                             0\n"
          ]
        }
      ],
      "source": [
        "def data_qualityCheck():\n",
        "    print(\"{:{}}\".format(\"\\033[1mCOLUMN\\033[0m\",38),end='')\n",
        "    print(\"{:{}}\".format(\"\\033[1mNULL VALUES COUNT\\033[0m\",18))\n",
        "    for x in train_df.columns:\n",
        "        print(\"{:{}}\".format(x,34),end='')\n",
        "        print(train_df[x].isnull().sum())\n",
        "\n",
        "\n",
        "data_qualityCheck()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.337061Z",
          "iopub.status.busy": "2021-05-25T06:50:32.336735Z",
          "iopub.status.idle": "2021-05-25T06:50:32.367948Z",
          "shell.execute_reply": "2021-05-25T06:50:32.366933Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.33703Z"
        },
        "id": "bncAge7hVOiA"
      },
      "outputs": [],
      "source": [
        "train_df=train_df.drop([\"id\", \"author\"], axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.401314Z",
          "iopub.status.busy": "2021-05-25T06:50:32.400868Z",
          "iopub.status.idle": "2021-05-25T06:50:32.407806Z",
          "shell.execute_reply": "2021-05-25T06:50:32.406589Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.401272Z"
        },
        "id": "-RYqM9y8VOiA",
        "outputId": "6593a6e5-935c-4791-b763-8ccc112c26f6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(20800, 3)"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_df.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 214
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.409912Z",
          "iopub.status.busy": "2021-05-25T06:50:32.409162Z",
          "iopub.status.idle": "2021-05-25T06:50:32.426843Z",
          "shell.execute_reply": "2021-05-25T06:50:32.425727Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.409868Z"
        },
        "id": "uYehrQvBVOiA",
        "outputId": "c6eb4d29-5690-4059-95a9-c929dd755f15"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"train_df\",\n  \"rows\": 20800,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 19803,\n        \"samples\": [\n          \"Florida Republicans Voting for Hillary Clinton \\u00b7 Guardian Liberty Voice\",\n          \"\\u2018Weekend Warriors\\u2019 Show Survival Benefits - The New York Times\",\n          \"Part 6, Democratic Network Money: Commons Money that Works for Us, Instead of Us Working for It\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20386,\n        \"samples\": [\n          \"Multan a un ultrasur por lanzar a un jugador del Bar\\u00e7a al campo durante el partido Madrid-Legia EL PARTIDO SE CONSIDERABA DE ALTO RIESGO PARA LOS JUGADORES DEL BARCELONA Real Madrid \\nUn jugador barcelonista golpe\\u00f3 a varios jugadores durante el encuentro de la Champions que tuvo lugar ayer entre el Real Madrid y el Legia Varsovia despu\\u00e9s de ser arrojado desde la grada por un hincha madridista. \\nEl portero del Legia, muy molesto, intent\\u00f3 devolver el jugador a las gradas de una patada y se encar\\u00f3 con los Ultrasur, que ya preparaban a otro jugador para echarlo al campo y entorpecer el encuentro. En esta ocasi\\u00f3n pretend\\u00edan prenderlo con un mechero antes de lanzarlo al c\\u00e9sped. \\nLas autoridades han vuelto a pedir a los aficionados que dejen de lanzar cosas al campo como botellas, monedas y jugadores del Barcelona. El dispositivo de seguridad no puedo hacer nada por evitar que algunos hinchas introdujeran a jugadores barcelonistas a la grada, pues los llevaban camuflados dentro de bocadillos de gran tama\\u00f1o. \\nEl partido pudo ser reanudado cuando el \\u00e1rbitro apart\\u00f3 a un rinc\\u00f3n del c\\u00e9sped al jugador barcelonista.\",\n          \"Written by Jacob G. Hornberger   As US officials continue to accuse Russia of meddling with the US presidential election, an accusation that they have provided no evidence whatsoever to support, let\\u2019s review some of the US government\\u2019s history of meddling with elections in others countries.1. In 1951, the democratically elected parliament of Iran elected a man named Mohammad Mossadegh to be Iran\\u2019s prime minister. Mossadegh angered British Empire officials by nationalizing British oil interests in the country.British officials then turned to the CIA for assistance. In 1953, the CIA secretly fomented a violent coup in Iran, which succeeded in ousting Mossadegh from power and making the Shah of Iran the supreme unelected dictator of the country.To fortify the Shah\\u2019s dictatorial hold on power, the CIA helped organize and train the his domestic police force, the Savak, which was essentially a combination of the CIA, the NSA, and the military. Part of the CIA\\u2019s training involved teaching Savak agents the art of torture.For the next 26 years, the Iranian people suffered under one of the most brutal and tyrannical dictatorships in the world, one that US officials fully supported and called an ally and friend of the United States.In 1979, Iranians successfully revolted against the Shah\\u2019s regime and ousted him from power. One result was not a restoration of the democratic system that had elected Mossadegh but rather another brutal dictatorship, this time a religious one. Another result is the bad relations between the Iran and US governments that continues to exist today.2. In 1951, the Guatemalan people democratically elected a man named Jacobo Arbenz to be their president. Arbenz, however, was not satisfactory to US officials, especially the national-security branch of the government, specifically the Pentagon and the CIA. The reason that US officials opposed Arbenz was that he was a socialist, and US officials considered a socialist president of Guatemala to be a threat to \\u201cnational security\\u201d here in the United States.In 1954 \\u2014 one year after the coup in Iran, the CIA fomented a violent military coup that succeeded in removing Arbenz from power and replacing him with one of the most brutal unelected military dictators in Latin American history, a man named Carlos Castillo Armas. The CIA had a kill list prepared for the coup, which Arbenz was able to escape by fleeing the country before Castillo was able to get him. The CIA\\u2019s destruction of Guatemala\\u2019s democratic system threw the nation into a 30-year civil war that ended up killing millions of Guatemalan people, especially many of the poor.3. In 1960 a man named Patrice Lamumba was elected Congo\\u2019s first prime minister after independence from Belgium. Lamumba spoke out against Western imperialism and refused to take sides in the Cold War, which caused the CIA to conclude that he was a threat to \\u201cnational security.\\u201d The CIA orchestrated the assassination of Lamumba, which ended up taking place on January 17, 1961, just three days before President Kennedy, who liked Lamumba and who would have ordered the CIA to stand down, was to be sworn into office.4. In 1970 a man named Salvador Allende received a plurality of votes in the presidential election in Chile. Pursuant to the Chilean constitution, the election was thrown into the national congress. President Richard Nixon, his national-security team, the Pentagon, and the CIA concluded that because Allende believed in communism and socialism, he posed a grave threat to \\u201cnational security\\u201d here in the United States. The CIA attempted to bribe members of the congress to vote against Allende. It also orchestrated the kidnapping of the head of Chile\\u2019s armed forces, Gen Rene Schneider, who opposed a US military coup in his country, especially since a coup would violate the country\\u2019s constitution. The kidnapping attempt on Schneider left him dead.The CIA then fomented a coup that took place on 9/11 1973 that violently ousted Allende from power and left him dead. Replacing him was army Gen. Augusto Pinochet, one of the most brutal unelected military dictators in history. By the time Pinochet\\u2019s 17-year reign of military terror came to an end in 1990, he and his CIA-supported goons had incarcerated, raped, tortured, or killed tens of thousands of innocent people \\u2014 that is, people whose only \\u201ccrime\\u201d was believing in socialism \\u2014 with the full support of the CIA, Pentagon, Nixon, and his \\u201cnational security\\u201d team.Of course, there are also the more recent support of regime-change operations that ousted democratically elected presidents that the US government disapproved of, such as in Ukraine and Egypt.And then there is the long list of countries where unelected dictators were targeted for regime change by the US national security state and, where successful, replaced with a brutal unelected pro-US dictator. Cuba, Indonesia, Iraq, Libya, and Syria all come to mind.US officials need to keep in mind that when they point their accusatory index finger at Russia for supposedly meddling in the US presidential election, US officials have, at the same time, three fingers pointing back at themselves. Reprinted with permission from the Future of Freedom Foundation . Related\",\n          \"When hearing of an establishment called the Black and Blue Steakhouse, one could reasonably surmise that some, or at the very least one, extremely tough person could be found somewhere in there. Well, the three terrorists who attacked London Bridge over the weekend found the Black and Blue Steakhouse, and they found the toughest man in the house. [Or, maybe more to the point, he found them.  Roy Larner, 47, is a huge fan of the South East London soccer team Millwall F. C. The team is known as the Lions, and when   terrorists entered the Black and Blue to kill innocent people, Larner let them know who is the true king of the jungle. After the terrorists entered, with obvious bad intentions, Larner sprang into action: \\u201cLike an idiot I shouted back at them. I thought, \\u2018I need to take the p*** out of these b*****s.\\u2019 \\u201cI took a few steps towards them and said, \\u2018F*** you, I\\u2019m Millwall.\\u2019 So they started attacking me. \\u201cI stood in front of them trying to fight them off. Everyone else ran to the back. I was on my own against all three of them, that\\u2019s why I got hurt so much. It was just me, trying to grab them with my bare hands and hold on. I was swinging. \\u201cI got stabbed and sliced eight times. They got me in my head, chest and both hands. There was blood everywhere. \\u201cThey were saying, \\u2018Islam, Islam!\\u2019 I said again, \\u2018F*** you, I\\u2019m Millwall!\\u2019 \\u201cIt was the worst thing I could have done as they carried on attacking me. \\u201cLuckily, none of the blows were straight at me or I\\u2019d be dead. \\u201d A petition has begun, with the aim of awarding Larner with the George Cross for bravery. The award is the second highest commendation granted by Great Britain. Looking at his scars, it\\u2019s really hard to imagine that he won\\u2019t get it. If Millwall is looking for a new slogan, they may have found it. \\u201cF*** you, I\\u2019m Millwall!\\u201d has a nice ring to it. Follow Dylan Gwinn on Twitter: @themightygwinn\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"label\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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              "                                               title  \\\n",
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        "label_train"
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              "summary": "{\n  \"name\": \"train_df\",\n  \"rows\": 20800,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 19803,\n        \"samples\": [\n          \"Florida Republicans Voting for Hillary Clinton \\u00b7 Guardian Liberty Voice\",\n          \"\\u2018Weekend Warriors\\u2019 Show Survival Benefits - The New York Times\",\n          \"Part 6, Democratic Network Money: Commons Money that Works for Us, Instead of Us Working for It\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20386,\n        \"samples\": [\n          \"Multan a un ultrasur por lanzar a un jugador del Bar\\u00e7a al campo durante el partido Madrid-Legia EL PARTIDO SE CONSIDERABA DE ALTO RIESGO PARA LOS JUGADORES DEL BARCELONA Real Madrid \\nUn jugador barcelonista golpe\\u00f3 a varios jugadores durante el encuentro de la Champions que tuvo lugar ayer entre el Real Madrid y el Legia Varsovia despu\\u00e9s de ser arrojado desde la grada por un hincha madridista. \\nEl portero del Legia, muy molesto, intent\\u00f3 devolver el jugador a las gradas de una patada y se encar\\u00f3 con los Ultrasur, que ya preparaban a otro jugador para echarlo al campo y entorpecer el encuentro. En esta ocasi\\u00f3n pretend\\u00edan prenderlo con un mechero antes de lanzarlo al c\\u00e9sped. \\nLas autoridades han vuelto a pedir a los aficionados que dejen de lanzar cosas al campo como botellas, monedas y jugadores del Barcelona. El dispositivo de seguridad no puedo hacer nada por evitar que algunos hinchas introdujeran a jugadores barcelonistas a la grada, pues los llevaban camuflados dentro de bocadillos de gran tama\\u00f1o. \\nEl partido pudo ser reanudado cuando el \\u00e1rbitro apart\\u00f3 a un rinc\\u00f3n del c\\u00e9sped al jugador barcelonista.\",\n          \"Written by Jacob G. Hornberger   As US officials continue to accuse Russia of meddling with the US presidential election, an accusation that they have provided no evidence whatsoever to support, let\\u2019s review some of the US government\\u2019s history of meddling with elections in others countries.1. In 1951, the democratically elected parliament of Iran elected a man named Mohammad Mossadegh to be Iran\\u2019s prime minister. Mossadegh angered British Empire officials by nationalizing British oil interests in the country.British officials then turned to the CIA for assistance. In 1953, the CIA secretly fomented a violent coup in Iran, which succeeded in ousting Mossadegh from power and making the Shah of Iran the supreme unelected dictator of the country.To fortify the Shah\\u2019s dictatorial hold on power, the CIA helped organize and train the his domestic police force, the Savak, which was essentially a combination of the CIA, the NSA, and the military. Part of the CIA\\u2019s training involved teaching Savak agents the art of torture.For the next 26 years, the Iranian people suffered under one of the most brutal and tyrannical dictatorships in the world, one that US officials fully supported and called an ally and friend of the United States.In 1979, Iranians successfully revolted against the Shah\\u2019s regime and ousted him from power. One result was not a restoration of the democratic system that had elected Mossadegh but rather another brutal dictatorship, this time a religious one. Another result is the bad relations between the Iran and US governments that continues to exist today.2. In 1951, the Guatemalan people democratically elected a man named Jacobo Arbenz to be their president. Arbenz, however, was not satisfactory to US officials, especially the national-security branch of the government, specifically the Pentagon and the CIA. The reason that US officials opposed Arbenz was that he was a socialist, and US officials considered a socialist president of Guatemala to be a threat to \\u201cnational security\\u201d here in the United States.In 1954 \\u2014 one year after the coup in Iran, the CIA fomented a violent military coup that succeeded in removing Arbenz from power and replacing him with one of the most brutal unelected military dictators in Latin American history, a man named Carlos Castillo Armas. The CIA had a kill list prepared for the coup, which Arbenz was able to escape by fleeing the country before Castillo was able to get him. The CIA\\u2019s destruction of Guatemala\\u2019s democratic system threw the nation into a 30-year civil war that ended up killing millions of Guatemalan people, especially many of the poor.3. In 1960 a man named Patrice Lamumba was elected Congo\\u2019s first prime minister after independence from Belgium. Lamumba spoke out against Western imperialism and refused to take sides in the Cold War, which caused the CIA to conclude that he was a threat to \\u201cnational security.\\u201d The CIA orchestrated the assassination of Lamumba, which ended up taking place on January 17, 1961, just three days before President Kennedy, who liked Lamumba and who would have ordered the CIA to stand down, was to be sworn into office.4. In 1970 a man named Salvador Allende received a plurality of votes in the presidential election in Chile. Pursuant to the Chilean constitution, the election was thrown into the national congress. President Richard Nixon, his national-security team, the Pentagon, and the CIA concluded that because Allende believed in communism and socialism, he posed a grave threat to \\u201cnational security\\u201d here in the United States. The CIA attempted to bribe members of the congress to vote against Allende. It also orchestrated the kidnapping of the head of Chile\\u2019s armed forces, Gen Rene Schneider, who opposed a US military coup in his country, especially since a coup would violate the country\\u2019s constitution. The kidnapping attempt on Schneider left him dead.The CIA then fomented a coup that took place on 9/11 1973 that violently ousted Allende from power and left him dead. Replacing him was army Gen. Augusto Pinochet, one of the most brutal unelected military dictators in history. By the time Pinochet\\u2019s 17-year reign of military terror came to an end in 1990, he and his CIA-supported goons had incarcerated, raped, tortured, or killed tens of thousands of innocent people \\u2014 that is, people whose only \\u201ccrime\\u201d was believing in socialism \\u2014 with the full support of the CIA, Pentagon, Nixon, and his \\u201cnational security\\u201d team.Of course, there are also the more recent support of regime-change operations that ousted democratically elected presidents that the US government disapproved of, such as in Ukraine and Egypt.And then there is the long list of countries where unelected dictators were targeted for regime change by the US national security state and, where successful, replaced with a brutal unelected pro-US dictator. Cuba, Indonesia, Iraq, Libya, and Syria all come to mind.US officials need to keep in mind that when they point their accusatory index finger at Russia for supposedly meddling in the US presidential election, US officials have, at the same time, three fingers pointing back at themselves. Reprinted with permission from the Future of Freedom Foundation . Related\",\n          \"When hearing of an establishment called the Black and Blue Steakhouse, one could reasonably surmise that some, or at the very least one, extremely tough person could be found somewhere in there. Well, the three terrorists who attacked London Bridge over the weekend found the Black and Blue Steakhouse, and they found the toughest man in the house. [Or, maybe more to the point, he found them.  Roy Larner, 47, is a huge fan of the South East London soccer team Millwall F. C. The team is known as the Lions, and when   terrorists entered the Black and Blue to kill innocent people, Larner let them know who is the true king of the jungle. After the terrorists entered, with obvious bad intentions, Larner sprang into action: \\u201cLike an idiot I shouted back at them. I thought, \\u2018I need to take the p*** out of these b*****s.\\u2019 \\u201cI took a few steps towards them and said, \\u2018F*** you, I\\u2019m Millwall.\\u2019 So they started attacking me. \\u201cI stood in front of them trying to fight them off. Everyone else ran to the back. I was on my own against all three of them, that\\u2019s why I got hurt so much. It was just me, trying to grab them with my bare hands and hold on. I was swinging. \\u201cI got stabbed and sliced eight times. They got me in my head, chest and both hands. There was blood everywhere. \\u201cThey were saying, \\u2018Islam, Islam!\\u2019 I said again, \\u2018F*** you, I\\u2019m Millwall!\\u2019 \\u201cIt was the worst thing I could have done as they carried on attacking me. \\u201cLuckily, none of the blows were straight at me or I\\u2019d be dead. \\u201d A petition has begun, with the aim of awarding Larner with the George Cross for bravery. The award is the second highest commendation granted by Great Britain. Looking at his scars, it\\u2019s really hard to imagine that he won\\u2019t get it. If Millwall is looking for a new slogan, they may have found it. \\u201cF*** you, I\\u2019m Millwall!\\u201d has a nice ring to it. Follow Dylan Gwinn on Twitter: @themightygwinn\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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            "text/plain": [
              "                                               title  \\\n",
              "0  House Dem Aide: We Didn’t Even See Comey’s Let...   \n",
              "1  FLYNN: Hillary Clinton, Big Woman on Campus - ...   \n",
              "2                  Why the Truth Might Get You Fired   \n",
              "3  15 Civilians Killed In Single US Airstrike Hav...   \n",
              "4  Iranian woman jailed for fictional unpublished...   \n",
              "5  Jackie Mason: Hollywood Would Love Trump if He...   \n",
              "6  Life: Life Of Luxury: Elton John’s 6 Favorite ...   \n",
              "7  Benoît Hamon Wins French Socialist Party’s Pre...   \n",
              "8  Excerpts From a Draft Script for Donald Trump’...   \n",
              "9  A Back-Channel Plan for Ukraine and Russia, Co...   \n",
              "\n",
              "                                                text  \n",
              "0  House Dem Aide: We Didn’t Even See Comey’s Let...  \n",
              "1  Ever get the feeling your life circles the rou...  \n",
              "2  Why the Truth Might Get You Fired October 29, ...  \n",
              "3  Videos 15 Civilians Killed In Single US Airstr...  \n",
              "4  Print \\nAn Iranian woman has been sentenced to...  \n",
              "5  In these trying times, Jackie Mason is the Voi...  \n",
              "6  Ever wonder how Britain’s most iconic pop pian...  \n",
              "7  PARIS  —   France chose an idealistic, traditi...  \n",
              "8  Donald J. Trump is scheduled to make a highly ...  \n",
              "9  A week before Michael T. Flynn resigned as nat...  "
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          "execution_count": 18,
          "metadata": {},
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    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "bwcszAF0VOiB"
      },
      "outputs": [],
      "source": [
        "def fill_data(data):\n",
        "    data[\"title\"] = data[\"title\"].fillna(\"Has No Title\")\n",
        "    data[\"text\"] = data[\"text\"].fillna(\"Has No text\")\n",
        "    return data\n",
        "\n",
        "train_df= fill_data(train_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vytXE12hVOiB",
        "outputId": "fb93d657-a61b-4119-9029-946b00f15b96"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[1mCOLUMN\u001b[0m                        \u001b[1mNULL VALUES COUNT\u001b[0m\n",
            "title                             0\n",
            "text                              0\n"
          ]
        }
      ],
      "source": [
        "data_qualityCheck()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 702
        },
        "id": "ZjIVE_AZVOiC",
        "outputId": "5f98c1b5-15a8-4404-9f55-5190f06d1b5b"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"train_df\",\n  \"rows\": 20800,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 19804,\n        \"samples\": [\n          \"Florida Republicans Voting for Hillary Clinton \\u00b7 Guardian Liberty Voice\",\n          \"A Suit Over Schiele Drawings Invokes New Law on Nazi-Looted Art - The New York Times\",\n          \"MMR Vaccines Cause 340% Increased Risk of Autism in African American Infants\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20387,\n        \"samples\": [\n          \"Multan a un ultrasur por lanzar a un jugador del Bar\\u00e7a al campo durante el partido Madrid-Legia EL PARTIDO SE CONSIDERABA DE ALTO RIESGO PARA LOS JUGADORES DEL BARCELONA Real Madrid \\nUn jugador barcelonista golpe\\u00f3 a varios jugadores durante el encuentro de la Champions que tuvo lugar ayer entre el Real Madrid y el Legia Varsovia despu\\u00e9s de ser arrojado desde la grada por un hincha madridista. \\nEl portero del Legia, muy molesto, intent\\u00f3 devolver el jugador a las gradas de una patada y se encar\\u00f3 con los Ultrasur, que ya preparaban a otro jugador para echarlo al campo y entorpecer el encuentro. En esta ocasi\\u00f3n pretend\\u00edan prenderlo con un mechero antes de lanzarlo al c\\u00e9sped. \\nLas autoridades han vuelto a pedir a los aficionados que dejen de lanzar cosas al campo como botellas, monedas y jugadores del Barcelona. El dispositivo de seguridad no puedo hacer nada por evitar que algunos hinchas introdujeran a jugadores barcelonistas a la grada, pues los llevaban camuflados dentro de bocadillos de gran tama\\u00f1o. \\nEl partido pudo ser reanudado cuando el \\u00e1rbitro apart\\u00f3 a un rinc\\u00f3n del c\\u00e9sped al jugador barcelonista.\",\n          \"Written by Eric Margolis   As a former soldier and war correspondent who has covered 14 conflicts, I look at all the media hoopla over tightening siege of Mosul, Iraq and shake my head. This western-organized \\u201cliberation\\u201d of Mosul is one of the bigger pieces of political-military theater that I\\u2019ve seen. Islamic State (IS), the defender of Mosul, is a paper tiger, blown out of all proportion by western media. IS is, as this writer has been saying for years, an armed mob made up of 20-something malcontents, religious fanatics, and modern-day anarchists. At its top is a cadre of former Iraqi Army officers with military experience. These former officers of Saddam Hussain are bent on revenge for the US destruction of their nation and the lynching of its late leader. But IS rank and file has no military training, little discipline, degraded communications, and ragged logistics. In fact, today\\u2019s Islamic State is what the Ottoman Empire used to term, \\u2018bashi-bazouks,\\u201d a collection of irregular cut-throats and scum of the gutter sent to punish and terrorize enemies by means of torture, rapine, looting, and arson. What has amazed me about the faux western war against ISIS is its leisurely nature, lack of \\u00e9lan , and hesitancy. In my view, ISIS was mostly created by the US and its allies as a weapon to be used against Syria\\u2019s government \\u2013 just as the Afghan mujahadin were used by the US and the Saudis to overthrow the Soviet-backed Afghan government. Israel tried the same tactics by helping create Hamas in Palestine and Hezbollah in Lebanon. Both were cultivated to split the PLO. ISIS is an ad hoc movement that wants to punish the West and the Saudis for the gross carnage they have inflicted on the Arab world. Western and Kurdish auxiliary forces have been sitting 1.5 hours drive from Mosul and the IS town of Raqqa for over a year. Instead, western \\u2013 mainly US \\u2013 warplanes have been gingerly bombing around these targets in what may be an effort to convince breakaway ISIS to rejoin US-led forces fight the Damascus regime. Note that ISIS does not appear to have ever attacked Israel though it is playing an important role in the destruction of Syria. Some reports say Israel is providing logistic and medical support for IS. The siege of Mosul is being played up by western media as a heroic second Stalingrad. Don\\u2019t be fooled. IS has only 3-5,000 lightly armed fighters in Mosul and Raqqa, maybe even less. The leaders of IS are likely long gone. IS has few heavy weapons, no air cover at all, and poor communications. Its rag-tag fighters will run out of ammunitions and explosives very quickly. Encircling Mosul are at least 50,000 western-led soldiers, backed by heavy artillery, rocket batteries, tanks, armored vehicles and awesome air power The western imperial forces are composed of tough Kurdish peshmerga fighters, Iraqi army and special forces, some Syrian Kurds, Iranian \\u2018volunteers\\u2019 irregular forces and at least 5,000 US combat troops called \\u201cadvisors\\u201d, plus small numbers of French, Canadian and British special forces. Hovering in the background are some thousands of Turkish troops, supported by armor and artillery ready to \\\"liberate\\\" Iraq \\u2013 which was once part of the Ottoman Empire. For the US, current military operations in Syria and Iraq are the realization of an imperialist\\u2019s fondest dream: native troops led by white officers, the model of the old British Indian Raj. Washington arms, trained, equips and financed all its native auxiliaries. The IS is caught in a dangerous dilemma. To be a political movement, it was delighted to control Iraq\\u2019s second largest city. But as a guerilla force, it should not have holed up in an urban area where it was highly vulnerable to concentrated air attack and being surrounded. This is what\\u2019s happening right now. In the mostly flat Fertile Crescent with too few trees, ground forces are totally vulnerable to air power, as the recent 1967, 1973 Israel-Arab wars and 2003 Iraq wars have shown. Dispersion and guerilla tactics are the only hope for those that lack air cover. IS forces would best advise to disperse across the region and continue their hit-and-run attacks. Otherwise, they risk being destroyed. But being mostly bloody-minded young fanatics, IS may not heed military logic and precedent in favor of making a last stand in the ruins of Mosul and Raqqa. When this happens, western leaders will compete to claim authorship of the faux crusade against the paper tiger of ISIS.   LewRockwell.com . Related\",\n          \"The   at the Democratic National Committee after an embarrassing breach of its email system continued on Tuesday with the departure of three senior officials. Amy Dacey, the committee\\u2019s chief executive Luis Miranda, its communications director and Brad Marshall, its chief financial officer, will leave amid a reshuffling of leadership positions, said Donna Brazile, the interim chairwoman. The departures came more than a week after WikiLeaks posted almost 20, 000 of the committee\\u2019s emails, a number of which revealed officials showing favoritism toward Hillary Clinton in her primary campaign against Senator Bernie Sanders of Vermont. The messages confirmed the concerns expressed by Mr. Sanders throughout the campaign, cast a cloud over the start of the Democratic National Convention in Philadelphia last week and led to the resignation of Representative Debbie Wasserman Schultz of Florida as the committee\\u2019s chairwoman. Ms. Brazile praised the outgoing staff members and made no mention of the controversy. \\u201cThanks in part to the hard work of Amy, Luis, and Brad, the Democratic Party has adopted the most progressive platform in history, has put itself in financial position to win in November, and has begun the important work of investing in state party partnerships,\\u201d she said in a statement. \\u201cI\\u2019m so grateful for their commitment to this cause, and I wish them continued success in the next chapter of their career. \\u201d American intelligence officials believe that the Russian government was behind the breach of the committee\\u2019s emails and documents, possibly as part of an effort to damage Mrs. Clinton and sow discord in the Democratic Party. An email from Mr. Marshall to Mark Paustenbach, a communications official, and Ms. Dacey suggesting that the committee promote questions about Mr. Sanders\\u2019s faith drew particular scorn from the senator and his supporters. \\u201cIt might may no difference, but for KY and WVA can we get someone to ask his belief. Does he believe in a God,\\u201d Mr. Marshall wrote, referring to Kentucky and West Virginia. \\u201cHe had skated on saying he has a Jewish heritage. I think I read he is an atheist. This could make several points difference with my peeps. \\u201d In May, Mr. Paustenbach wrote to Mr. Miranda about encouraging reporters to write that Mr. Sanders\\u2019s campaign was \\u201ca mess\\u201d after a glitch on the committee\\u2019s servers gave the Sanders campaign access to the Clinton campaign\\u2019s voter database. \\u201cWondering if there\\u2019s a good Bernie narrative for a story, which is that Bernie never ever had his act together, that his campaign was a mess,\\u201d Mr. Paustenbach wrote. Mr. Miranda wrote back: \\u201cTrue, but the Chair has been advised to not engage. So we\\u2019ll have to leave it alone. \\u201d The committee has since apologized to the Sanders campaign. To help fill the void, the committee announced, it is bringing on Tom McMahon, a former executive director of the committee, to lead a transition team.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "train_df"
            },
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "      height: 32px;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-830a3676-b1be-4cef-afa6-44e16ed03b1e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-830a3676-b1be-4cef-afa6-44e16ed03b1e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "\n",
              "\n",
              "<div id=\"df-867241d4-ecdc-4951-a6f6-6937e0dfcc57\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-867241d4-ecdc-4951-a6f6-6937e0dfcc57')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-867241d4-ecdc-4951-a6f6-6937e0dfcc57 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "                                                title  \\\n",
              "0   House Dem Aide: We Didn’t Even See Comey’s Let...   \n",
              "1   FLYNN: Hillary Clinton, Big Woman on Campus - ...   \n",
              "2                   Why the Truth Might Get You Fired   \n",
              "3   15 Civilians Killed In Single US Airstrike Hav...   \n",
              "4   Iranian woman jailed for fictional unpublished...   \n",
              "5   Jackie Mason: Hollywood Would Love Trump if He...   \n",
              "6   Life: Life Of Luxury: Elton John’s 6 Favorite ...   \n",
              "7   Benoît Hamon Wins French Socialist Party’s Pre...   \n",
              "8   Excerpts From a Draft Script for Donald Trump’...   \n",
              "9   A Back-Channel Plan for Ukraine and Russia, Co...   \n",
              "10  Obama’s Organizing for Action Partners with So...   \n",
              "11  BBC Comedy Sketch \"Real Housewives of ISIS\" Ca...   \n",
              "12  Russian Researchers Discover Secret Nazi Milit...   \n",
              "13  US Officials See No Link Between Trump and Russia   \n",
              "14  Re: Yes, There Are Paid Government Trolls On S...   \n",
              "15  In Major League Soccer, Argentines Find a Home...   \n",
              "16  Wells Fargo Chief Abruptly Steps Down - The Ne...   \n",
              "17  Anonymous Donor Pays $2.5 Million To Release E...   \n",
              "18                          FBI Closes In On Hillary!   \n",
              "19  Chuck Todd: ’BuzzFeed Did Donald Trump a Polit...   \n",
              "\n",
              "                                                 text  \n",
              "0   House Dem Aide: We Didn’t Even See Comey’s Let...  \n",
              "1   Ever get the feeling your life circles the rou...  \n",
              "2   Why the Truth Might Get You Fired October 29, ...  \n",
              "3   Videos 15 Civilians Killed In Single US Airstr...  \n",
              "4   Print \\nAn Iranian woman has been sentenced to...  \n",
              "5   In these trying times, Jackie Mason is the Voi...  \n",
              "6   Ever wonder how Britain’s most iconic pop pian...  \n",
              "7   PARIS  —   France chose an idealistic, traditi...  \n",
              "8   Donald J. Trump is scheduled to make a highly ...  \n",
              "9   A week before Michael T. Flynn resigned as nat...  \n",
              "10  Organizing for Action, the activist group that...  \n",
              "11  The BBC produced spoof on the “Real Housewives...  \n",
              "12  The mystery surrounding The Third Reich and Na...  \n",
              "13  Clinton Campaign Demands FBI Affirm Trump's Ru...  \n",
              "14  Yes, There Are Paid Government Trolls On Socia...  \n",
              "15  Guillermo Barros Schelotto was not the first A...  \n",
              "16  The scandal engulfing Wells Fargo toppled its ...  \n",
              "17  A Caddo Nation tribal leader has just been fre...  \n",
              "18  FBI Closes In On Hillary! Posted on Home » Hea...  \n",
              "19  Wednesday after   Donald Trump’s press confere...  "
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_df.head(20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "fIA0Iz43VOiC"
      },
      "outputs": [],
      "source": [
        "train_df[\"new_text\"] = train_df[\"title\"] + \" \" + train_df[\"text\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 758
        },
        "id": "C45iZk35VOiC",
        "outputId": "12f5f028-3b13-4546-b138-33e5ab3e60f7"
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              "summary": "{\n  \"name\": \"train_df\",\n  \"rows\": 20800,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 19804,\n        \"samples\": [\n          \"Florida Republicans Voting for Hillary Clinton \\u00b7 Guardian Liberty Voice\",\n          \"A Suit Over Schiele Drawings Invokes New Law on Nazi-Looted Art - The New York Times\",\n          \"MMR Vaccines Cause 340% Increased Risk of Autism in African American Infants\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20387,\n        \"samples\": [\n          \"Multan a un ultrasur por lanzar a un jugador del Bar\\u00e7a al campo durante el partido Madrid-Legia EL PARTIDO SE CONSIDERABA DE ALTO RIESGO PARA LOS JUGADORES DEL BARCELONA Real Madrid \\nUn jugador barcelonista golpe\\u00f3 a varios jugadores durante el encuentro de la Champions que tuvo lugar ayer entre el Real Madrid y el Legia Varsovia despu\\u00e9s de ser arrojado desde la grada por un hincha madridista. \\nEl portero del Legia, muy molesto, intent\\u00f3 devolver el jugador a las gradas de una patada y se encar\\u00f3 con los Ultrasur, que ya preparaban a otro jugador para echarlo al campo y entorpecer el encuentro. En esta ocasi\\u00f3n pretend\\u00edan prenderlo con un mechero antes de lanzarlo al c\\u00e9sped. \\nLas autoridades han vuelto a pedir a los aficionados que dejen de lanzar cosas al campo como botellas, monedas y jugadores del Barcelona. El dispositivo de seguridad no puedo hacer nada por evitar que algunos hinchas introdujeran a jugadores barcelonistas a la grada, pues los llevaban camuflados dentro de bocadillos de gran tama\\u00f1o. \\nEl partido pudo ser reanudado cuando el \\u00e1rbitro apart\\u00f3 a un rinc\\u00f3n del c\\u00e9sped al jugador barcelonista.\",\n          \"Written by Eric Margolis   As a former soldier and war correspondent who has covered 14 conflicts, I look at all the media hoopla over tightening siege of Mosul, Iraq and shake my head. This western-organized \\u201cliberation\\u201d of Mosul is one of the bigger pieces of political-military theater that I\\u2019ve seen. Islamic State (IS), the defender of Mosul, is a paper tiger, blown out of all proportion by western media. IS is, as this writer has been saying for years, an armed mob made up of 20-something malcontents, religious fanatics, and modern-day anarchists. At its top is a cadre of former Iraqi Army officers with military experience. These former officers of Saddam Hussain are bent on revenge for the US destruction of their nation and the lynching of its late leader. But IS rank and file has no military training, little discipline, degraded communications, and ragged logistics. In fact, today\\u2019s Islamic State is what the Ottoman Empire used to term, \\u2018bashi-bazouks,\\u201d a collection of irregular cut-throats and scum of the gutter sent to punish and terrorize enemies by means of torture, rapine, looting, and arson. What has amazed me about the faux western war against ISIS is its leisurely nature, lack of \\u00e9lan , and hesitancy. In my view, ISIS was mostly created by the US and its allies as a weapon to be used against Syria\\u2019s government \\u2013 just as the Afghan mujahadin were used by the US and the Saudis to overthrow the Soviet-backed Afghan government. Israel tried the same tactics by helping create Hamas in Palestine and Hezbollah in Lebanon. Both were cultivated to split the PLO. ISIS is an ad hoc movement that wants to punish the West and the Saudis for the gross carnage they have inflicted on the Arab world. Western and Kurdish auxiliary forces have been sitting 1.5 hours drive from Mosul and the IS town of Raqqa for over a year. Instead, western \\u2013 mainly US \\u2013 warplanes have been gingerly bombing around these targets in what may be an effort to convince breakaway ISIS to rejoin US-led forces fight the Damascus regime. Note that ISIS does not appear to have ever attacked Israel though it is playing an important role in the destruction of Syria. Some reports say Israel is providing logistic and medical support for IS. The siege of Mosul is being played up by western media as a heroic second Stalingrad. Don\\u2019t be fooled. IS has only 3-5,000 lightly armed fighters in Mosul and Raqqa, maybe even less. The leaders of IS are likely long gone. IS has few heavy weapons, no air cover at all, and poor communications. Its rag-tag fighters will run out of ammunitions and explosives very quickly. Encircling Mosul are at least 50,000 western-led soldiers, backed by heavy artillery, rocket batteries, tanks, armored vehicles and awesome air power The western imperial forces are composed of tough Kurdish peshmerga fighters, Iraqi army and special forces, some Syrian Kurds, Iranian \\u2018volunteers\\u2019 irregular forces and at least 5,000 US combat troops called \\u201cadvisors\\u201d, plus small numbers of French, Canadian and British special forces. Hovering in the background are some thousands of Turkish troops, supported by armor and artillery ready to \\\"liberate\\\" Iraq \\u2013 which was once part of the Ottoman Empire. For the US, current military operations in Syria and Iraq are the realization of an imperialist\\u2019s fondest dream: native troops led by white officers, the model of the old British Indian Raj. Washington arms, trained, equips and financed all its native auxiliaries. The IS is caught in a dangerous dilemma. To be a political movement, it was delighted to control Iraq\\u2019s second largest city. But as a guerilla force, it should not have holed up in an urban area where it was highly vulnerable to concentrated air attack and being surrounded. This is what\\u2019s happening right now. In the mostly flat Fertile Crescent with too few trees, ground forces are totally vulnerable to air power, as the recent 1967, 1973 Israel-Arab wars and 2003 Iraq wars have shown. Dispersion and guerilla tactics are the only hope for those that lack air cover. IS forces would best advise to disperse across the region and continue their hit-and-run attacks. Otherwise, they risk being destroyed. But being mostly bloody-minded young fanatics, IS may not heed military logic and precedent in favor of making a last stand in the ruins of Mosul and Raqqa. When this happens, western leaders will compete to claim authorship of the faux crusade against the paper tiger of ISIS.   LewRockwell.com . Related\",\n          \"The   at the Democratic National Committee after an embarrassing breach of its email system continued on Tuesday with the departure of three senior officials. Amy Dacey, the committee\\u2019s chief executive Luis Miranda, its communications director and Brad Marshall, its chief financial officer, will leave amid a reshuffling of leadership positions, said Donna Brazile, the interim chairwoman. The departures came more than a week after WikiLeaks posted almost 20, 000 of the committee\\u2019s emails, a number of which revealed officials showing favoritism toward Hillary Clinton in her primary campaign against Senator Bernie Sanders of Vermont. The messages confirmed the concerns expressed by Mr. Sanders throughout the campaign, cast a cloud over the start of the Democratic National Convention in Philadelphia last week and led to the resignation of Representative Debbie Wasserman Schultz of Florida as the committee\\u2019s chairwoman. Ms. Brazile praised the outgoing staff members and made no mention of the controversy. \\u201cThanks in part to the hard work of Amy, Luis, and Brad, the Democratic Party has adopted the most progressive platform in history, has put itself in financial position to win in November, and has begun the important work of investing in state party partnerships,\\u201d she said in a statement. \\u201cI\\u2019m so grateful for their commitment to this cause, and I wish them continued success in the next chapter of their career. \\u201d American intelligence officials believe that the Russian government was behind the breach of the committee\\u2019s emails and documents, possibly as part of an effort to damage Mrs. Clinton and sow discord in the Democratic Party. An email from Mr. Marshall to Mark Paustenbach, a communications official, and Ms. Dacey suggesting that the committee promote questions about Mr. Sanders\\u2019s faith drew particular scorn from the senator and his supporters. \\u201cIt might may no difference, but for KY and WVA can we get someone to ask his belief. Does he believe in a God,\\u201d Mr. Marshall wrote, referring to Kentucky and West Virginia. \\u201cHe had skated on saying he has a Jewish heritage. I think I read he is an atheist. This could make several points difference with my peeps. \\u201d In May, Mr. Paustenbach wrote to Mr. Miranda about encouraging reporters to write that Mr. Sanders\\u2019s campaign was \\u201ca mess\\u201d after a glitch on the committee\\u2019s servers gave the Sanders campaign access to the Clinton campaign\\u2019s voter database. \\u201cWondering if there\\u2019s a good Bernie narrative for a story, which is that Bernie never ever had his act together, that his campaign was a mess,\\u201d Mr. Paustenbach wrote. Mr. Miranda wrote back: \\u201cTrue, but the Chair has been advised to not engage. So we\\u2019ll have to leave it alone. \\u201d The committee has since apologized to the Sanders campaign. To help fill the void, the committee announced, it is bringing on Tom McMahon, a former executive director of the committee, to lead a transition team.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"new_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20690,\n        \"samples\": [\n          \"Italy to Speed up Migrant Asylum Decisions, Deportations ROME (AP)  \\u2014   The Italian government on Friday approved measures aimed at streamlining the decision process for asylum requests  \\u2014   as well as speeding up the deportations of those whose asylum bids have been denied. [advertisement\",\n          \"Hillary Clinton Laughs When Asked If the New Emails Could Sink Her Campaign By Sarah Jones on Fri, Oct 28th, 2016 at 8:02 pm Secretary Clinton put pressure on Comey to explain himself saying, \\\"We've heard these rumors, we don't know what to believe. That is why it is incumbent on the FBI to tell us what they are talking about.\\\" Asked if she thought this could sink her campaign, Clinton laughed. Share on Twitter Print This Post \\nHillary Clinton did a quick presser in Iowa to respond to questions about the FBI Director James Comey\\u2019s decision to appear to violate the Hatch Act 11 by participating in political activities 11 days before an election. \\nSecretary Clinton put pressure on Comey to explain himself saying, \\u201cWe\\u2019ve heard these rumors, we don\\u2019t know what to believe. That is why it is incumbent on the FBI to tell us what they are talking about.\\u201d \\nWatch here: Video: Hillary Clinton calls on FBI to release all of the info it has & explain the issue in question without delay https://t.co/rg57U1RqPf \\n\\u2014 Bradd Jaffy (@BraddJaffy) October 28, 2016 \\n\\u201cThe American people deserve to get the full and complete facts immediately. The director himself has said he doesn\\u2019t know if the emails referenced in his letter are significant or not,\\u201d the Democratic nominee said. \\n\\u201cThat\\u2019s why it\\u2019s incumbent on the FBI to tell us what they\\u2019re talking about,\\u201d Clinton said. \\nClinton pushed for more information to be released \\u201cwithout delay.\\u201d She said she found about the investigation from reports and that she wasn\\u2019t given advance notice. Clinton said she had not been contacted by Comey on this issue. \\nWhen asked what she would tell voters about her emails, Clinton responded, \\u201cI think people made up their minds a while ago about the emails.\\u201d \\nThis might be the right place to mention the 22 million emails the Bush administration \\u201clost\\u201d and the private RNC servers they used, as context for how important this issue really is to Republicans as a value. \\nKristen Welker asked if Clinton was afraid that this could sink her campaign, to which Secretary Clinton responded with a big laugh: \\\"Are you worried this could sink your campaign, Secretary Clinton,\\\" a reporter shouts as HRC walks out. Clinton only lets out a big laugh. \\n\\u2014 Ruby Cramer (@rubycramer) October 28, 2016 \\nThe Republican FBI Director James Comey wrote the House on Friday to inform hopeful Republicans that they had found new emails relating to Clinton\\u2019s private email that begged further investigation. \\nIt turns out the emails didn\\u2019t come from Clinton\\u2019s server and there doesn\\u2019t seem to be any there there, except for giving Republicans a reason their base needs to get out to vote. \\nFederal employees are forbidden from participating in political activities under the Hatch Act, and this is why a complaint has already been lodged against Comey . \\nHillary Clinton laughed because what else is she supposed to do at this point. How many years on is this? Republicans have mined this hopeful scandal for so long it\\u2019s DOA. The press has followed Republicans\\u2019 lead with the absurd email story- a story as ridiculous as it is common, and a story that was never a story until Clinton did it. \\nRepublicans and some in the press think this might sink the Clinton campaign. So they think America would rather put Putin\\u2019s puppet who laughs about sexually assaulting women in the White House than someone whose emails we\\u2019ve all read now and found nothing much but gossip. \\nYeah, I don\\u2019t think so. \\nDead story was dead before it started, but that won\\u2019t stop it from being spun into blood match.\",\n          \"Liberty Links 10/29/16 Post was not sent - check your email addresses! Email check failed, please try again Sorry, your blog cannot share posts by email.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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              "      <td>15 Civilians Killed In Single US Airstrike Hav...</td>\n",
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              "      <td>Iranian woman jailed for fictional unpublished...</td>\n",
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              "      <td>A Back-Channel Plan for Ukraine and Russia, Co...</td>\n",
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              "      <td>Obama’s Organizing for Action Partners with So...</td>\n",
              "      <td>Organizing for Action, the activist group that...</td>\n",
              "      <td>Obama’s Organizing for Action Partners with So...</td>\n",
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              "      <td>The BBC produced spoof on the “Real Housewives...</td>\n",
              "      <td>BBC Comedy Sketch \"Real Housewives of ISIS\" Ca...</td>\n",
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            "text/plain": [
              "                                                title  \\\n",
              "0   House Dem Aide: We Didn’t Even See Comey’s Let...   \n",
              "1   FLYNN: Hillary Clinton, Big Woman on Campus - ...   \n",
              "2                   Why the Truth Might Get You Fired   \n",
              "3   15 Civilians Killed In Single US Airstrike Hav...   \n",
              "4   Iranian woman jailed for fictional unpublished...   \n",
              "5   Jackie Mason: Hollywood Would Love Trump if He...   \n",
              "6   Life: Life Of Luxury: Elton John’s 6 Favorite ...   \n",
              "7   Benoît Hamon Wins French Socialist Party’s Pre...   \n",
              "8   Excerpts From a Draft Script for Donald Trump’...   \n",
              "9   A Back-Channel Plan for Ukraine and Russia, Co...   \n",
              "10  Obama’s Organizing for Action Partners with So...   \n",
              "11  BBC Comedy Sketch \"Real Housewives of ISIS\" Ca...   \n",
              "12  Russian Researchers Discover Secret Nazi Milit...   \n",
              "13  US Officials See No Link Between Trump and Russia   \n",
              "14  Re: Yes, There Are Paid Government Trolls On S...   \n",
              "15  In Major League Soccer, Argentines Find a Home...   \n",
              "16  Wells Fargo Chief Abruptly Steps Down - The Ne...   \n",
              "17  Anonymous Donor Pays $2.5 Million To Release E...   \n",
              "18                          FBI Closes In On Hillary!   \n",
              "19  Chuck Todd: ’BuzzFeed Did Donald Trump a Polit...   \n",
              "\n",
              "                                                 text  \\\n",
              "0   House Dem Aide: We Didn’t Even See Comey’s Let...   \n",
              "1   Ever get the feeling your life circles the rou...   \n",
              "2   Why the Truth Might Get You Fired October 29, ...   \n",
              "3   Videos 15 Civilians Killed In Single US Airstr...   \n",
              "4   Print \\nAn Iranian woman has been sentenced to...   \n",
              "5   In these trying times, Jackie Mason is the Voi...   \n",
              "6   Ever wonder how Britain’s most iconic pop pian...   \n",
              "7   PARIS  —   France chose an idealistic, traditi...   \n",
              "8   Donald J. Trump is scheduled to make a highly ...   \n",
              "9   A week before Michael T. Flynn resigned as nat...   \n",
              "10  Organizing for Action, the activist group that...   \n",
              "11  The BBC produced spoof on the “Real Housewives...   \n",
              "12  The mystery surrounding The Third Reich and Na...   \n",
              "13  Clinton Campaign Demands FBI Affirm Trump's Ru...   \n",
              "14  Yes, There Are Paid Government Trolls On Socia...   \n",
              "15  Guillermo Barros Schelotto was not the first A...   \n",
              "16  The scandal engulfing Wells Fargo toppled its ...   \n",
              "17  A Caddo Nation tribal leader has just been fre...   \n",
              "18  FBI Closes In On Hillary! Posted on Home » Hea...   \n",
              "19  Wednesday after   Donald Trump’s press confere...   \n",
              "\n",
              "                                             new_text  \n",
              "0   House Dem Aide: We Didn’t Even See Comey’s Let...  \n",
              "1   FLYNN: Hillary Clinton, Big Woman on Campus - ...  \n",
              "2   Why the Truth Might Get You Fired Why the Trut...  \n",
              "3   15 Civilians Killed In Single US Airstrike Hav...  \n",
              "4   Iranian woman jailed for fictional unpublished...  \n",
              "5   Jackie Mason: Hollywood Would Love Trump if He...  \n",
              "6   Life: Life Of Luxury: Elton John’s 6 Favorite ...  \n",
              "7   Benoît Hamon Wins French Socialist Party’s Pre...  \n",
              "8   Excerpts From a Draft Script for Donald Trump’...  \n",
              "9   A Back-Channel Plan for Ukraine and Russia, Co...  \n",
              "10  Obama’s Organizing for Action Partners with So...  \n",
              "11  BBC Comedy Sketch \"Real Housewives of ISIS\" Ca...  \n",
              "12  Russian Researchers Discover Secret Nazi Milit...  \n",
              "13  US Officials See No Link Between Trump and Rus...  \n",
              "14  Re: Yes, There Are Paid Government Trolls On S...  \n",
              "15  In Major League Soccer, Argentines Find a Home...  \n",
              "16  Wells Fargo Chief Abruptly Steps Down - The Ne...  \n",
              "17  Anonymous Donor Pays $2.5 Million To Release E...  \n",
              "18  FBI Closes In On Hillary! FBI Closes In On Hil...  \n",
              "19  Chuck Todd: ’BuzzFeed Did Donald Trump a Polit...  "
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_df.head(20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "id": "989Gn_54VOiC"
      },
      "outputs": [],
      "source": [
        "train_df=train_df.drop(['title','text'],axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 214
        },
        "id": "Jb8rimDsVOiC",
        "outputId": "b591f3e1-386f-4bdf-fd24-b1f769f936e8"
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      "outputs": [
        {
          "data": {
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              "summary": "{\n  \"name\": \"train_df\",\n  \"rows\": 20800,\n  \"fields\": [\n    {\n      \"column\": \"new_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20690,\n        \"samples\": [\n          \"Italy to Speed up Migrant Asylum Decisions, Deportations ROME (AP)  \\u2014   The Italian government on Friday approved measures aimed at streamlining the decision process for asylum requests  \\u2014   as well as speeding up the deportations of those whose asylum bids have been denied. [advertisement\",\n          \"Hillary Clinton Laughs When Asked If the New Emails Could Sink Her Campaign By Sarah Jones on Fri, Oct 28th, 2016 at 8:02 pm Secretary Clinton put pressure on Comey to explain himself saying, \\\"We've heard these rumors, we don't know what to believe. That is why it is incumbent on the FBI to tell us what they are talking about.\\\" Asked if she thought this could sink her campaign, Clinton laughed. Share on Twitter Print This Post \\nHillary Clinton did a quick presser in Iowa to respond to questions about the FBI Director James Comey\\u2019s decision to appear to violate the Hatch Act 11 by participating in political activities 11 days before an election. \\nSecretary Clinton put pressure on Comey to explain himself saying, \\u201cWe\\u2019ve heard these rumors, we don\\u2019t know what to believe. That is why it is incumbent on the FBI to tell us what they are talking about.\\u201d \\nWatch here: Video: Hillary Clinton calls on FBI to release all of the info it has & explain the issue in question without delay https://t.co/rg57U1RqPf \\n\\u2014 Bradd Jaffy (@BraddJaffy) October 28, 2016 \\n\\u201cThe American people deserve to get the full and complete facts immediately. The director himself has said he doesn\\u2019t know if the emails referenced in his letter are significant or not,\\u201d the Democratic nominee said. \\n\\u201cThat\\u2019s why it\\u2019s incumbent on the FBI to tell us what they\\u2019re talking about,\\u201d Clinton said. \\nClinton pushed for more information to be released \\u201cwithout delay.\\u201d She said she found about the investigation from reports and that she wasn\\u2019t given advance notice. Clinton said she had not been contacted by Comey on this issue. \\nWhen asked what she would tell voters about her emails, Clinton responded, \\u201cI think people made up their minds a while ago about the emails.\\u201d \\nThis might be the right place to mention the 22 million emails the Bush administration \\u201clost\\u201d and the private RNC servers they used, as context for how important this issue really is to Republicans as a value. \\nKristen Welker asked if Clinton was afraid that this could sink her campaign, to which Secretary Clinton responded with a big laugh: \\\"Are you worried this could sink your campaign, Secretary Clinton,\\\" a reporter shouts as HRC walks out. Clinton only lets out a big laugh. \\n\\u2014 Ruby Cramer (@rubycramer) October 28, 2016 \\nThe Republican FBI Director James Comey wrote the House on Friday to inform hopeful Republicans that they had found new emails relating to Clinton\\u2019s private email that begged further investigation. \\nIt turns out the emails didn\\u2019t come from Clinton\\u2019s server and there doesn\\u2019t seem to be any there there, except for giving Republicans a reason their base needs to get out to vote. \\nFederal employees are forbidden from participating in political activities under the Hatch Act, and this is why a complaint has already been lodged against Comey . \\nHillary Clinton laughed because what else is she supposed to do at this point. How many years on is this? Republicans have mined this hopeful scandal for so long it\\u2019s DOA. The press has followed Republicans\\u2019 lead with the absurd email story- a story as ridiculous as it is common, and a story that was never a story until Clinton did it. \\nRepublicans and some in the press think this might sink the Clinton campaign. So they think America would rather put Putin\\u2019s puppet who laughs about sexually assaulting women in the White House than someone whose emails we\\u2019ve all read now and found nothing much but gossip. \\nYeah, I don\\u2019t think so. \\nDead story was dead before it started, but that won\\u2019t stop it from being spun into blood match.\",\n          \"Liberty Links 10/29/16 Post was not sent - check your email addresses! Email check failed, please try again Sorry, your blog cannot share posts by email.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-01821874-6c48-4586-b6f9-8fc08a4fe634 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                            new_text\n",
              "0  House Dem Aide: We Didn’t Even See Comey’s Let...\n",
              "1  FLYNN: Hillary Clinton, Big Woman on Campus - ...\n",
              "2  Why the Truth Might Get You Fired Why the Trut...\n",
              "3  15 Civilians Killed In Single US Airstrike Hav...\n",
              "4  Iranian woman jailed for fictional unpublished..."
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "sHxwW_i8VOiD"
      },
      "outputs": [],
      "source": [
        "custom_download_dir = \"C:\\\\Users\\\\ysach/nltk\"\n",
        "nltk.data.path.append(custom_download_dir)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VY9tFLbiVOiD",
        "outputId": "61de6128-676a-495c-a88e-30c462781f7a"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package stopwords to C:\\Users\\ysach/nltk...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "nltk.download('stopwords',download_dir=custom_download_dir)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.51602Z",
          "iopub.status.busy": "2021-05-25T06:50:32.515411Z",
          "iopub.status.idle": "2021-05-25T06:50:32.531829Z",
          "shell.execute_reply": "2021-05-25T06:50:32.530895Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.515972Z"
        },
        "id": "z_szVbR6VOiD"
      },
      "outputs": [],
      "source": [
        "lemmatizer = WordNetLemmatizer()\n",
        "stpwrds = list(stopwords.words('english'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o2N0UJRNVOiD",
        "outputId": "e410e2fa-98d9-4a82-f853-7d2a5fb6829d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['i',\n",
              " 'me',\n",
              " 'my',\n",
              " 'myself',\n",
              " 'we',\n",
              " 'our',\n",
              " 'ours',\n",
              " 'ourselves',\n",
              " 'you',\n",
              " \"you're\",\n",
              " \"you've\",\n",
              " \"you'll\",\n",
              " \"you'd\",\n",
              " 'your',\n",
              " 'yours',\n",
              " 'yourself',\n",
              " 'yourselves',\n",
              " 'he',\n",
              " 'him',\n",
              " 'his',\n",
              " 'himself',\n",
              " 'she',\n",
              " \"she's\",\n",
              " 'her',\n",
              " 'hers',\n",
              " 'herself',\n",
              " 'it',\n",
              " \"it's\",\n",
              " 'its',\n",
              " 'itself',\n",
              " 'they',\n",
              " 'them',\n",
              " 'their',\n",
              " 'theirs',\n",
              " 'themselves',\n",
              " 'what',\n",
              " 'which',\n",
              " 'who',\n",
              " 'whom',\n",
              " 'this',\n",
              " 'that',\n",
              " \"that'll\",\n",
              " 'these',\n",
              " 'those',\n",
              " 'am',\n",
              " 'is',\n",
              " 'are',\n",
              " 'was',\n",
              " 'were',\n",
              " 'be',\n",
              " 'been',\n",
              " 'being',\n",
              " 'have',\n",
              " 'has',\n",
              " 'had',\n",
              " 'having',\n",
              " 'do',\n",
              " 'does',\n",
              " 'did',\n",
              " 'doing',\n",
              " 'a',\n",
              " 'an',\n",
              " 'the',\n",
              " 'and',\n",
              " 'but',\n",
              " 'if',\n",
              " 'or',\n",
              " 'because',\n",
              " 'as',\n",
              " 'until',\n",
              " 'while',\n",
              " 'of',\n",
              " 'at',\n",
              " 'by',\n",
              " 'for',\n",
              " 'with',\n",
              " 'about',\n",
              " 'against',\n",
              " 'between',\n",
              " 'into',\n",
              " 'through',\n",
              " 'during',\n",
              " 'before',\n",
              " 'after',\n",
              " 'above',\n",
              " 'below',\n",
              " 'to',\n",
              " 'from',\n",
              " 'up',\n",
              " 'down',\n",
              " 'in',\n",
              " 'out',\n",
              " 'on',\n",
              " 'off',\n",
              " 'over',\n",
              " 'under',\n",
              " 'again',\n",
              " 'further',\n",
              " 'then',\n",
              " 'once',\n",
              " 'here',\n",
              " 'there',\n",
              " 'when',\n",
              " 'where',\n",
              " 'why',\n",
              " 'how',\n",
              " 'all',\n",
              " 'any',\n",
              " 'both',\n",
              " 'each',\n",
              " 'few',\n",
              " 'more',\n",
              " 'most',\n",
              " 'other',\n",
              " 'some',\n",
              " 'such',\n",
              " 'no',\n",
              " 'nor',\n",
              " 'not',\n",
              " 'only',\n",
              " 'own',\n",
              " 'same',\n",
              " 'so',\n",
              " 'than',\n",
              " 'too',\n",
              " 'very',\n",
              " 's',\n",
              " 't',\n",
              " 'can',\n",
              " 'will',\n",
              " 'just',\n",
              " 'don',\n",
              " \"don't\",\n",
              " 'should',\n",
              " \"should've\",\n",
              " 'now',\n",
              " 'd',\n",
              " 'll',\n",
              " 'm',\n",
              " 'o',\n",
              " 're',\n",
              " 've',\n",
              " 'y',\n",
              " 'ain',\n",
              " 'aren',\n",
              " \"aren't\",\n",
              " 'couldn',\n",
              " \"couldn't\",\n",
              " 'didn',\n",
              " \"didn't\",\n",
              " 'doesn',\n",
              " \"doesn't\",\n",
              " 'hadn',\n",
              " \"hadn't\",\n",
              " 'hasn',\n",
              " \"hasn't\",\n",
              " 'haven',\n",
              " \"haven't\",\n",
              " 'isn',\n",
              " \"isn't\",\n",
              " 'ma',\n",
              " 'mightn',\n",
              " \"mightn't\",\n",
              " 'mustn',\n",
              " \"mustn't\",\n",
              " 'needn',\n",
              " \"needn't\",\n",
              " 'shan',\n",
              " \"shan't\",\n",
              " 'shouldn',\n",
              " \"shouldn't\",\n",
              " 'wasn',\n",
              " \"wasn't\",\n",
              " 'weren',\n",
              " \"weren't\",\n",
              " 'won',\n",
              " \"won't\",\n",
              " 'wouldn',\n",
              " \"wouldn't\"]"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "stpwrds"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4_An9jM8VOiD",
        "outputId": "05131e3f-6443-4d7c-a9a0-b5886bf9f2f4"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package punkt to C:\\Users\\ysach/nltk...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n",
            "[nltk_data] Downloading package wordnet to C:\\Users\\ysach/nltk...\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "nltk.download('punkt',download_dir=custom_download_dir)\n",
        "nltk.download('wordnet',download_dir=custom_download_dir)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7AsHgN5QVOiD",
        "outputId": "b0d6a4ef-bbd0-46e6-bb64-0ae2d7e27566"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package omw-1.4 to C:\\Users\\ysach/nltk...\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 31,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "nltk.download('omw-1.4',download_dir=custom_download_dir)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-05-25T06:50:32.54905Z",
          "iopub.status.busy": "2021-05-25T06:50:32.548517Z",
          "iopub.status.idle": "2021-05-25T06:53:51.648153Z",
          "shell.execute_reply": "2021-05-25T06:53:51.647283Z",
          "shell.execute_reply.started": "2021-05-25T06:50:32.549015Z"
        },
        "id": "TBi1QmMvVOiE"
      },
      "outputs": [],
      "source": [
        "for x in range(len(train_df)) :\n",
        "    corpus = []\n",
        "    review = train_df['new_text'][x]\n",
        "    review = re.sub(r'[^a-zA-Z\\s]', '', review)\n",
        "    review = review.lower()\n",
        "    review = nltk.word_tokenize(review)\n",
        "    for y in review :\n",
        "        if y not in stpwrds :\n",
        "            corpus.append(lemmatizer.lemmatize(y))\n",
        "    review = ' '.join(corpus)\n",
        "    train_df['new_text'][x] = review"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T07:14:51.798724Z",
          "iopub.status.busy": "2021-05-25T07:14:51.798361Z",
          "iopub.status.idle": "2021-05-25T07:14:51.805617Z",
          "shell.execute_reply": "2021-05-25T07:14:51.804946Z",
          "shell.execute_reply.started": "2021-05-25T07:14:51.798694Z"
        },
        "id": "DUsJPQ-zVOiE",
        "outputId": "da32ca68-edc9-4937-9e3a-dd9de3c974ae",
        "scrolled": true
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'actor steven seagal live tv erupts hillary obama intense comment actor steven seagal stood america rest hollywood remains silent week rough country first democratic nominee hillary clinton collapsed memorial called million hardworking american deplorable werent enough nfl player throughout country blatantly disrespecting american flag needle say seagal enough think important job secretary state ensuring people dont get killed seagal tweeted cant email protected pneumonia going disastrous american people notohillary continued course seagal quickly became target liberal fire comment refused break particularly lost one twitter user tried argued hillary capable presidency capable capable leaving american die capable disregarding law capable disrespecting rape survivor argued went address race relation united state true role president barack obama played social evolution country obama abysmal race relation usa truth need start honest dialog wrote seagal concluded pointing irony attack receiving liberal everywhere best thing worldmaking one statement freedom getting attacked every demo hypocritical tweeted america without democrat white house safer america think seagals comment'"
            ]
          },
          "execution_count": 33,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "train_df['new_text'][2188]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CK2JdnmdVOiE",
        "outputId": "ec842d3c-69e7-46ff-d58f-21c96fee7116"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "execution_count": 34,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "label_train[2188]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-05-25T07:16:37.152728Z",
          "iopub.status.busy": "2021-05-25T07:16:37.152216Z",
          "iopub.status.idle": "2021-05-25T07:16:37.163059Z",
          "shell.execute_reply": "2021-05-25T07:16:37.161884Z",
          "shell.execute_reply.started": "2021-05-25T07:16:37.152696Z"
        },
        "id": "A7-GS-boVOiE"
      },
      "outputs": [],
      "source": [
        "X_train= train_df['new_text']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B4B4E7YnVOiE",
        "outputId": "5d868b19-baae-4176-9014-60075074c21d",
        "scrolled": true
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0        house dem aide didnt even see comeys letter ja...\n",
              "1        flynn hillary clinton big woman campus breitba...\n",
              "2        truth might get fired truth might get fired oc...\n",
              "3        civilian killed single u airstrike identified ...\n",
              "4        iranian woman jailed fictional unpublished sto...\n",
              "                               ...                        \n",
              "20795    rapper ti trump poster child white supremacy r...\n",
              "20796    nfl playoff schedule matchup odds new york tim...\n",
              "20797    macys said receive takeover approach hudson ba...\n",
              "20798    nato russia hold parallel exercise balkan nato...\n",
              "20799    keep f alive david swanson author activist jou...\n",
              "Name: new_text, Length: 20800, dtype: object"
            ]
          },
          "execution_count": 36,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "X_train"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T07:17:50.592597Z",
          "iopub.status.busy": "2021-05-25T07:17:50.592095Z",
          "iopub.status.idle": "2021-05-25T07:17:50.598862Z",
          "shell.execute_reply": "2021-05-25T07:17:50.597641Z",
          "shell.execute_reply.started": "2021-05-25T07:17:50.592566Z"
        },
        "id": "sZa_xgnHVOiF",
        "outputId": "00dc263c-02c5-4ed4-8a38-b69683624577"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(20800,)"
            ]
          },
          "execution_count": 37,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "X_train.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T07:18:05.89317Z",
          "iopub.status.busy": "2021-05-25T07:18:05.892651Z",
          "iopub.status.idle": "2021-05-25T07:18:05.902743Z",
          "shell.execute_reply": "2021-05-25T07:18:05.901523Z",
          "shell.execute_reply.started": "2021-05-25T07:18:05.893127Z"
        },
        "id": "lVfIZR1EVOiF",
        "outputId": "a03ca4b0-8e9d-489e-c3c3-214d473781b8"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(20800,)"
            ]
          },
          "execution_count": 38,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "label_train.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "id": "55CGFAF3VOiF"
      },
      "outputs": [],
      "source": [
        "from keras.preprocessing.text import Tokenizer\n",
        "from keras.preprocessing.sequence import pad_sequences"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S8sdIqOBVOiF",
        "outputId": "087d77c9-54a1-4bb0-ba4f-42428ce9a1a5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The Padding Sequance Shape is  -->  (20800, 12140)\n"
          ]
        }
      ],
      "source": [
        "tokenize = Tokenizer(oov_token=\"<OOV>\")\n",
        "tokenize.fit_on_texts(X_train)\n",
        "word_idx = tokenize.word_index\n",
        "\n",
        "text2seq = tokenize.texts_to_sequences(X_train)\n",
        "\n",
        "# pad_seq = pad_sequences(text2seq, maxlen=150, padding=\"pre\", truncating=\"pre\")\n",
        "\n",
        "pad_seq = pad_sequences(text2seq, padding=\"pre\", truncating=\"pre\")\n",
        "\n",
        "\n",
        "print(\"The Padding Sequance Shape is  --> \", pad_seq.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "id": "p_8scqKxVOiF"
      },
      "outputs": [],
      "source": [
        "input_length = max(len(seq) for seq in text2seq)\n",
        "\n",
        "vocabulary_size = len(word_idx) + 1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4XJ3BI4UVOiF",
        "outputId": "1b629938-94f3-463f-c65e-422953386f3a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The maximum Sequance Length is  -->  12140\n",
            "The vocabulary size of dataset is  -->  166055\n"
          ]
        }
      ],
      "source": [
        "print(\"The maximum Sequance Length is  --> \", input_length)\n",
        "print(\"The vocabulary size of dataset is  --> \", vocabulary_size)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "id": "G0BuRpOxVOiL"
      },
      "outputs": [],
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "vectorizer = CountVectorizer(\n",
        "    ngram_range=(1,1),\n",
        "    max_features=250\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-05-25T07:18:10.901469Z",
          "iopub.status.busy": "2021-05-25T07:18:10.901136Z",
          "iopub.status.idle": "2021-05-25T07:18:22.003384Z",
          "shell.execute_reply": "2021-05-25T07:18:22.002314Z",
          "shell.execute_reply.started": "2021-05-25T07:18:10.90144Z"
        },
        "id": "aVxtNLrKVOiL"
      },
      "outputs": [],
      "source": [
        "#tfidf_v = TfidfVectorizer()\n",
        "#tfidf_X_train = vectorizer.fit_transform(X_train)\n",
        "#tfidf_X_test = vectorizer.transform(X_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-05-25T07:18:24.321674Z",
          "iopub.status.busy": "2021-05-25T07:18:24.321329Z",
          "iopub.status.idle": "2021-05-25T07:18:24.327063Z",
          "shell.execute_reply": "2021-05-25T07:18:24.325975Z",
          "shell.execute_reply.started": "2021-05-25T07:18:24.321644Z"
        },
        "id": "jPg27MZnVOiM"
      },
      "outputs": [],
      "source": [
        "#tfidf_X_train.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "execution": {
          "iopub.execute_input": "2021-05-25T07:18:31.418929Z",
          "iopub.status.busy": "2021-05-25T07:18:31.418573Z",
          "iopub.status.idle": "2021-05-25T07:18:31.427535Z",
          "shell.execute_reply": "2021-05-25T07:18:31.426865Z",
          "shell.execute_reply.started": "2021-05-25T07:18:31.418889Z"
        },
        "id": "K199y-qQVOiM"
      },
      "outputs": [],
      "source": [
        "def plot_confusion_matrix(cm, classes,\n",
        "                          normalize=False,\n",
        "                          title='Confusion matrix',\n",
        "                          cmap=plt.cm.GnBu):\n",
        "\n",
        "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
        "    plt.title(title)\n",
        "    plt.colorbar()\n",
        "    tick_marks = np.arange(len(classes))\n",
        "    plt.xticks(tick_marks, classes, rotation=45)\n",
        "    plt.yticks(tick_marks, classes)\n",
        "\n",
        "    if normalize:\n",
        "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
        "        print(\"Normalized confusion matrix\")\n",
        "    else:\n",
        "        print('Confusion matrix, without normalization')\n",
        "\n",
        "    thresh = cm.max() / 2.\n",
        "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
        "        plt.text(j, i, cm[i, j],\n",
        "                 horizontalalignment=\"center\",\n",
        "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.ylabel('True label')\n",
        "    plt.xlabel('Predicted label')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aFQrI8aTVOiM",
        "outputId": "c94157c6-793e-47d6-8827-05b39cb443d4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: tensorflow in /usr/local/lib/python3.10/dist-packages (2.15.0)\n",
            "Requirement already satisfied: absl-py>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (1.4.0)\n",
            "Requirement already satisfied: astunparse>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (1.6.3)\n",
            "Requirement already satisfied: flatbuffers>=23.5.26 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (24.3.25)\n",
            "Requirement already satisfied: gast!=0.5.0,!=0.5.1,!=0.5.2,>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (0.5.4)\n",
            "Requirement already satisfied: google-pasta>=0.1.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (0.2.0)\n",
            "Requirement already satisfied: h5py>=2.9.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (3.9.0)\n",
            "Requirement already satisfied: libclang>=13.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (18.1.1)\n",
            "Requirement already satisfied: ml-dtypes~=0.2.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (0.2.0)\n",
            "Requirement already satisfied: numpy<2.0.0,>=1.23.5 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (1.25.2)\n",
            "Requirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (3.3.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from tensorflow) (24.1)\n",
            "Requirement already satisfied: protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (3.20.3)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from tensorflow) (67.7.2)\n",
            "Requirement already satisfied: six>=1.12.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (1.16.0)\n",
            "Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (2.4.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.6 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (4.12.2)\n",
            "Requirement already satisfied: wrapt<1.15,>=1.11.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (1.14.1)\n",
            "Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (0.37.0)\n",
            "Requirement already satisfied: grpcio<2.0,>=1.24.3 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (1.64.1)\n",
            "Requirement already satisfied: tensorboard<2.16,>=2.15 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (2.15.2)\n",
            "Requirement already satisfied: tensorflow-estimator<2.16,>=2.15.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (2.15.0)\n",
            "Requirement already satisfied: keras<2.16,>=2.15.0 in /usr/local/lib/python3.10/dist-packages (from tensorflow) (2.15.0)\n",
            "Requirement already satisfied: wheel<1.0,>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from astunparse>=1.6.0->tensorflow) (0.43.0)\n",
            "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.16,>=2.15->tensorflow) (2.27.0)\n",
            "Requirement already satisfied: google-auth-oauthlib<2,>=0.5 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.16,>=2.15->tensorflow) (1.2.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.16,>=2.15->tensorflow) (3.6)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.16,>=2.15->tensorflow) (2.31.0)\n",
            "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.16,>=2.15->tensorflow) (0.7.2)\n",
            "Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard<2.16,>=2.15->tensorflow) (3.0.3)\n",
            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (5.3.3)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (0.4.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (4.9)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<2,>=0.5->tensorboard<2.16,>=2.15->tensorflow) (1.3.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (2024.6.2)\n",
            "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard<2.16,>=2.15->tensorflow) (2.1.5)\n",
            "Requirement already satisfied: pyasn1<0.7.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (0.6.0)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard<2.16,>=2.15->tensorflow) (3.2.2)\n"
          ]
        }
      ],
      "source": [
        "!pip install tensorflow"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "id": "yGouYK7uVOiM"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "id": "aOK2MeDJVOiM"
      },
      "outputs": [],
      "source": [
        "import keras\n",
        "from keras.models import Sequential\n",
        "from keras.utils import to_categorical\n",
        "from keras import metrics as metrics1\n",
        "from keras.layers import LeakyReLU\n",
        "from keras.layers import Dense, Embedding, GlobalAveragePooling1D, LSTM, Bidirectional"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "id": "VrradLHXVOiN"
      },
      "outputs": [],
      "source": [
        "x_train1, x_test, y_train1, y_test = train_test_split(pad_seq, label_train, train_size=0.7)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 52,
      "metadata": {
        "id": "2LR7NbuyVOiN"
      },
      "outputs": [],
      "source": [
        "classifier = Sequential()\n",
        "classifier.add(Embedding(vocabulary_size, 182, input_length=input_length))\n",
        "classifier.add(GlobalAveragePooling1D())\n",
        "classifier.add(Dense(96, activation='relu'))\n",
        "classifier.add(Dense(24, activation='relu'))\n",
        "classifier.add(Dense(1, activation='sigmoid'))\n",
        "\n",
        "# Compile the model\n",
        "classifier.compile(optimizer='adam',\n",
        "              loss='binary_crossentropy',\n",
        "              metrics=['accuracy'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zgiK46YTVOiN",
        "outputId": "28862f08-7dce-4f7a-cac0-6a81676a11b5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " embedding (Embedding)       (None, 12140, 182)        30222010  \n",
            "                                                                 \n",
            " global_average_pooling1d (  (None, 182)               0         \n",
            " GlobalAveragePooling1D)                                         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 96)                17568     \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 24)                2328      \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 1)                 25        \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 30241931 (115.36 MB)\n",
            "Trainable params: 30241931 (115.36 MB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "classifier.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XrET5Y7VVOiN",
        "outputId": "469df5d7-c23a-4e05-af14-0e01e3d1b562"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "455/455 [==============================] - 80s 171ms/step - loss: 0.6713 - accuracy: 0.5717 - val_loss: 0.5499 - val_accuracy: 0.7174\n",
            "Epoch 2/10\n",
            "455/455 [==============================] - 68s 148ms/step - loss: 0.3381 - accuracy: 0.8591 - val_loss: 0.3359 - val_accuracy: 0.8207\n",
            "Epoch 3/10\n",
            "455/455 [==============================] - 58s 127ms/step - loss: 0.1859 - accuracy: 0.9321 - val_loss: 0.1829 - val_accuracy: 0.9290\n",
            "Epoch 4/10\n",
            "455/455 [==============================] - 49s 107ms/step - loss: 0.1199 - accuracy: 0.9608 - val_loss: 0.1520 - val_accuracy: 0.9436\n",
            "Epoch 5/10\n",
            "455/455 [==============================] - 41s 91ms/step - loss: 0.0897 - accuracy: 0.9707 - val_loss: 0.1323 - val_accuracy: 0.9563\n",
            "Epoch 6/10\n",
            "455/455 [==============================] - 42s 92ms/step - loss: 0.0587 - accuracy: 0.9817 - val_loss: 0.1327 - val_accuracy: 0.9543\n",
            "Epoch 7/10\n",
            "455/455 [==============================] - 33s 74ms/step - loss: 0.0621 - accuracy: 0.9791 - val_loss: 0.1249 - val_accuracy: 0.9580\n",
            "Epoch 8/10\n",
            "455/455 [==============================] - 31s 68ms/step - loss: 0.0322 - accuracy: 0.9912 - val_loss: 0.1230 - val_accuracy: 0.9630\n",
            "Epoch 9/10\n",
            "455/455 [==============================] - 31s 69ms/step - loss: 0.0300 - accuracy: 0.9900 - val_loss: 0.1570 - val_accuracy: 0.9551\n",
            "Epoch 10/10\n",
            "455/455 [==============================] - 25s 55ms/step - loss: 0.0321 - accuracy: 0.9887 - val_loss: 0.1315 - val_accuracy: 0.9615\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x7cd1565dd090>"
            ]
          },
          "execution_count": 66,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "classifier.fit(x_train1,y_train1,epochs=10,validation_data=(x_test, y_test))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 67,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FXzLnv6aVOiN",
        "outputId": "9a2b60f4-7e8b-4731-b1ca-fe3b4a541b7e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "196/196 [==============================] - 1s 4ms/step\n"
          ]
        }
      ],
      "source": [
        "Y_pred = classifier.predict(x_test)\n",
        "a=[]\n",
        "for x in Y_pred:\n",
        "    if x>=0.5:\n",
        "        a.append(1)\n",
        "    else:\n",
        "        a.append(0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 68,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "execution": {
          "iopub.execute_input": "2021-05-25T07:18:41.422338Z",
          "iopub.status.busy": "2021-05-25T07:18:41.421887Z",
          "iopub.status.idle": "2021-05-25T07:18:41.673492Z",
          "shell.execute_reply": "2021-05-25T07:18:41.672498Z",
          "shell.execute_reply.started": "2021-05-25T07:18:41.422308Z"
        },
        "id": "ellLynyzVOiO",
        "outputId": "27d8e7cf-258d-4840-cf4f-9690efbd6f78"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy: 96.15%\n",
            "Confusion matrix, without normalization\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "score = accuracy_score(y_test, a)\n",
        "print(f'Accuracy: {round(score*100,2)}%')\n",
        "cm = confusion_matrix(y_test, a)\n",
        "plot_confusion_matrix(cm, classes=['FAKE Data', 'REAL Data'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 69,
      "metadata": {
        "id": "qcg0mtkqVOiO"
      },
      "outputs": [],
      "source": [
        "from keras.layers import SimpleRNN,LSTM"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 70,
      "metadata": {
        "id": "z9E5QuHjVOiO"
      },
      "outputs": [],
      "source": [
        "model = Sequential()\n",
        "model.add(Embedding(vocabulary_size, 100, input_length=input_length))\n",
        "model.add(SimpleRNN(units=10, return_sequences=False))\n",
        "model.add(Dense(units=1))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "metadata": {
        "id": "X71K1Sn9VOiO"
      },
      "outputs": [],
      "source": [
        "model.compile(optimizer='adam',\n",
        "              loss='binary_crossentropy',\n",
        "              metrics=['accuracy'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 72,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z9ydY-D1VOiO",
        "outputId": "974ce2b6-e089-4719-9434-e760819ec2ce"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"sequential_2\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " embedding_2 (Embedding)     (None, 12140, 100)        16605500  \n",
            "                                                                 \n",
            " simple_rnn_1 (SimpleRNN)    (None, 10)                1110      \n",
            "                                                                 \n",
            " dense_4 (Dense)             (None, 1)                 11        \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 16606621 (63.35 MB)\n",
            "Trainable params: 16606621 (63.35 MB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "model.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3SXRkzmXVOiP",
        "outputId": "a6857916-9d20-42d4-b58f-857ffc3412dd"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/3\n",
            "455/455 [==============================] - 2882s 6s/step - loss: 0.7130 - accuracy: 0.8058 - val_loss: 0.6941 - val_accuracy: 0.8763\n",
            "Epoch 2/3\n",
            "455/455 [==============================] - 3135s 7s/step - loss: 0.2564 - accuracy: 0.9559 - val_loss: 0.8114 - val_accuracy: 0.7906\n",
            "Epoch 3/3\n",
            "455/455 [==============================] - 3928s 9s/step - loss: 0.1439 - accuracy: 0.9792 - val_loss: 0.7665 - val_accuracy: 0.8503\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x1760ee6eec0>"
            ]
          },
          "execution_count": 72,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "model.fit(x_train1,y_train1,epochs=3,validation_data=(x_test, y_test))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7uev9RUxVOiP",
        "outputId": "6b22c956-9790-4c9b-ae40-1194b56dd097"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "196/196 [==============================] - 170s 864ms/step\n"
          ]
        }
      ],
      "source": [
        "Y_pred = model.predict(x_test)\n",
        "a=[]\n",
        "for x in Y_pred:\n",
        "    if x>=0.5:\n",
        "        a.append(1)\n",
        "    else:\n",
        "        a.append(0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "id": "i3Q-tiE4VOiP",
        "outputId": "35746810-304f-49f1-a102-fcf8406d9f36"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Accuracy: 50.2%\n",
            "Confusion matrix, without normalization\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#For second model\n",
        "score = accuracy_score(y_test, a)\n",
        "print(f'Accuracy: {round(score*100,2)}%')\n",
        "cm = confusion_matrix(y_test, a)\n",
        "plot_confusion_matrix(cm, classes=['FAKE Data', 'REAL Data'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "metadata": {
        "id": "7Vgb98dOVOiP"
      },
      "outputs": [],
      "source": [
        "#The first model performed better.The second model had good training accuracy but less test accuracy hinting towards overfitting.Maybe the key reason being in fake news it is important to capture overall sentiment better than individual word sentiment."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "metadata": {
        "id": "aNpXc-_iVOiP"
      },
      "outputs": [],
      "source": [
        "def fake_news_det(news):\n",
        "    review = news\n",
        "    review = re.sub(r'[^a-zA-Z\\s]', '', review)\n",
        "    review = review.lower()\n",
        "    review = nltk.word_tokenize(review)\n",
        "    for y in review :\n",
        "        if y not in stpwrds :\n",
        "            corpus.append(lemmatizer.lemmatize(y))\n",
        "    input_data = [' '.join(corpus)]\n",
        "    vectorized_input_data_pre = tokenize.texts_to_sequences(input_data)\n",
        "    vectorized_input_data=pad_sequences(vectorized_input_data_pre, padding=\"pre\", truncating=\"pre\")\n",
        "    prediction = classifier.predict(vectorized_input_data)\n",
        "    if prediction[0] == 1:\n",
        "        print(\"Prediction of the News :  Looking Fake⚠ News📰 \")\n",
        "    else:\n",
        "        print(\"Prediction of the News : Looking Real News📰 \")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L2PkL_N5VOiQ",
        "outputId": "ccda9d27-4f2e-4c64-de8e-3766bbcfa5ff"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "1/1 [==============================] - 0s 22ms/step\n",
            "Prediction of the News :  Looking Fake⚠ News📰 \n"
          ]
        }
      ],
      "source": [
        "fake_news_det(\"actor steven seagal live tv erupts hillary obama intense comment actor steven seagal stood america rest hollywood remains silent week rough country first democratic nominee hillary clinton collapsed memorial called million hardworking american deplorable werent enough nfl player throughout country blatantly disrespecting american flag needle say seagal enough think important job secretary state ensuring people dont get killed seagal tweeted cant email protected pneumonia going disastrous american people\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KGXYo-ABVUcz",
        "outputId": "b5df6f2b-ac0e-4dbe-e698-cee72400c649"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting gradio\n",
            "  Downloading gradio-4.36.1-py3-none-any.whl (12.3 MB)\n",
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            "Building wheels for collected packages: ffmpy\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=160f8e4fc7821fd5fb12f58b527b083946ce37f320d14962444fdede2f93ed51\n",
            "  Stored in directory: /root/.cache/pip/wheels/bd/65/9a/671fc6dcde07d4418df0c592f8df512b26d7a0029c2a23dd81\n",
            "Successfully built ffmpy\n",
            "Installing collected packages: pydub, ffmpy, websockets, uvloop, ujson, tomlkit, semantic-version, ruff, python-multipart, python-dotenv, orjson, httptools, h11, dnspython, aiofiles, watchfiles, uvicorn, starlette, httpcore, email_validator, httpx, gradio-client, fastapi-cli, fastapi, gradio\n",
            "Successfully installed aiofiles-23.2.1 dnspython-2.6.1 email_validator-2.1.1 fastapi-0.111.0 fastapi-cli-0.0.4 ffmpy-0.3.2 gradio-4.36.1 gradio-client-1.0.1 h11-0.14.0 httpcore-1.0.5 httptools-0.6.1 httpx-0.27.0 orjson-3.10.4 pydub-0.25.1 python-dotenv-1.0.1 python-multipart-0.0.9 ruff-0.4.8 semantic-version-2.10.0 starlette-0.37.2 tomlkit-0.12.0 ujson-5.10.0 uvicorn-0.30.1 uvloop-0.19.0 watchfiles-0.22.0 websockets-11.0.3\n"
          ]
        }
      ],
      "source": [
        "!pip install gradio"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AJEBWnTFYW5Z",
        "outputId": "863de178-c6d6-456f-baf7-5d8bd70509a7"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/usr/lib/python3.10/runpy.py:126: RuntimeWarning: 'nltk.downloader' found in sys.modules after import of package 'nltk', but prior to execution of 'nltk.downloader'; this may result in unpredictable behaviour\n",
            "  warn(RuntimeWarning(msg))\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n"
          ]
        }
      ],
      "source": [
        "!python -m nltk.downloader punkt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o_cyi1oh16i8",
        "outputId": "c9cf94ab-1536-440a-e323-dbc87ce532c4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6.0,>=4.2.0->gradio) (23.2.0)\n",
            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6.0,>=4.2.0->gradio) (2023.12.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6.0,>=4.2.0->gradio) (0.35.1)\n",
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            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->keras>=3.0.0->tensorflow) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->keras>=3.0.0->tensorflow) (2.16.1)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio->httpx>=0.24.1->gradio) (1.2.1)\n",
            "Requirement already satisfied: httptools>=0.5.0 in /usr/local/lib/python3.10/dist-packages (from uvicorn>=0.14.0->gradio) (0.6.1)\n",
            "Requirement already satisfied: python-dotenv>=0.13 in /usr/local/lib/python3.10/dist-packages (from uvicorn>=0.14.0->gradio) (1.0.1)\n",
            "Requirement already satisfied: uvloop!=0.15.0,!=0.15.1,>=0.14.0 in /usr/local/lib/python3.10/dist-packages (from uvicorn>=0.14.0->gradio) (0.19.0)\n",
            "Requirement already satisfied: watchfiles>=0.13 in /usr/local/lib/python3.10/dist-packages (from uvicorn>=0.14.0->gradio) (0.22.0)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->keras>=3.0.0->tensorflow) (0.1.2)\n",
            "Installing collected packages: namex, optree, ml-dtypes, h5py, tensorboard, keras, tensorflow\n",
            "  Attempting uninstall: ml-dtypes\n",
            "    Found existing installation: ml-dtypes 0.2.0\n",
            "    Uninstalling ml-dtypes-0.2.0:\n",
            "      Successfully uninstalled ml-dtypes-0.2.0\n",
            "  Attempting uninstall: h5py\n",
            "    Found existing installation: h5py 3.9.0\n",
            "    Uninstalling h5py-3.9.0:\n",
            "      Successfully uninstalled h5py-3.9.0\n",
            "  Attempting uninstall: tensorboard\n",
            "    Found existing installation: tensorboard 2.15.2\n",
            "    Uninstalling tensorboard-2.15.2:\n",
            "      Successfully uninstalled tensorboard-2.15.2\n",
            "  Attempting uninstall: keras\n",
            "    Found existing installation: keras 2.15.0\n",
            "    Uninstalling keras-2.15.0:\n",
            "      Successfully uninstalled keras-2.15.0\n",
            "  Attempting uninstall: tensorflow\n",
            "    Found existing installation: tensorflow 2.15.0\n",
            "    Uninstalling tensorflow-2.15.0:\n",
            "      Successfully uninstalled tensorflow-2.15.0\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "tf-keras 2.15.1 requires tensorflow<2.16,>=2.15, but you have tensorflow 2.16.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed h5py-3.11.0 keras-3.3.3 ml-dtypes-0.3.2 namex-0.0.8 optree-0.11.0 tensorboard-2.16.2 tensorflow-2.16.1\n"
          ]
        }
      ],
      "source": [
        "!pip install --upgrade gradio tensorflow"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "HgrmmTqXW5FZ"
      },
      "outputs": [],
      "source": [
        "from nltk.corpus import stopwords\n",
        "from nltk.stem.porter import PorterStemmer\n",
        "\n",
        "def preprocess_text(text):\n",
        "  text = text.lower()\n",
        "  tokens = text.split()\n",
        "  stop_words = set(stopwords.words('english'))\n",
        "  stemmer = PorterStemmer()\n",
        "\n",
        "  # Combine stemming and stop word removal:\n",
        "  preprocessed_text = [stemmer.stem(word) for word in tokens if word not in stop_words]\n",
        "  return ' '.join(preprocessed_text)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nLhx9h5JamKC",
        "outputId": "57adbbe9-6ce2-43a2-dcbd-974c0bb5d562"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive') #user can save the model in drive and can access drive with this\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "metadata": {
        "id": "T1aYakmkRzPI"
      },
      "outputs": [],
      "source": [
        "import pickle\n",
        "pickle.dump(classifier, open('/content/model1.pkl', 'wb')) #saving the model in .pkl format"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 80,
      "metadata": {
        "id": "XNNigvpQlgNC"
      },
      "outputs": [],
      "source": [
        "model_loaded = pickle.load(open('/content/model1.pkl', 'rb')) #loading the model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6xPiULlnlv9q",
        "outputId": "76554107-726b-437e-97b4-75a885cc36be"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "196/196 [==============================] - 1s 4ms/step\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "array([[6.7016238e-04],\n",
              "       [9.9623787e-01],\n",
              "       [9.9986446e-01],\n",
              "       ...,\n",
              "       [7.6568440e-09],\n",
              "       [9.9962425e-01],\n",
              "       [9.9963582e-01]], dtype=float32)"
            ]
          },
          "execution_count": 81,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "model_loaded.predict(x_test) #checking. whther model can predict or not."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 88,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JfYl6H7_p1_5",
        "outputId": "677eb9bf-39e3-418e-afc7-b23df1be5dbf"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "1/1 [==============================] - 0s 36ms/step\n",
            "Real News\n"
          ]
        }
      ],
      "source": [
        "def predict_fake_news(text):\n",
        "    review = text\n",
        "    review = re.sub(r'[^a-zA-Z\\s]', '', review)\n",
        "    review = review.lower()\n",
        "    review = nltk.word_tokenize(review)\n",
        "    for y in review :\n",
        "        if y not in stpwrds :\n",
        "            corpus.append(lemmatizer.lemmatize(y))\n",
        "    input_data = [' '.join(corpus)]\n",
        "    vectorized_input_data_pre = tokenize.texts_to_sequences(input_data)\n",
        "    vectorized_input_data=pad_sequences(vectorized_input_data_pre, padding=\"pre\", truncating=\"pre\")\n",
        "    prediction = model_loaded.predict(vectorized_input_data)  # Use your model here\n",
        "    return prediction\n",
        "\n",
        "text = \"Prime Minister Narendra Modi is all set for his first foreign visit after taking oath as the PM of India for the third consecutive term. He will travel to Apulia, Italy, on Thursday to participate in the 50th G7 Summit. The summit is scheduled to be held in Apulia from June 13 to June 15.\"\n",
        "score = predict_fake_news(text)\n",
        "if score>0.5:\n",
        "    print(\"Real News\")\n",
        "else:\n",
        "    print(\"Fake News\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 93,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 653
        },
        "id": "5UuzXsnvW7v1",
        "outputId": "af73a669-5b95-47f0-85df-500e04896674"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://bd96a007dcb8714da1.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div><iframe src=\"https://bd96a007dcb8714da1.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": []
          },
          "execution_count": 93,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import gradio as gr\n",
        "\n",
        "\n",
        "def fake_news_detector(text):\n",
        "    score = predict_fake_news(text)\n",
        "\n",
        "    classification = \"Real\" if score > 0.7 else \"Fake\"\n",
        "\n",
        "    output = (\n",
        "        f\"Classification: {classification}\"\n",
        "    )\n",
        "    return output\n",
        "\n",
        "\n",
        "interface = gr.Interface(\n",
        "    fake_news_detector,\n",
        "    inputs=\"textbox\",\n",
        "    outputs=\"text\",\n",
        "    title=\"Fake News Detector\",\n",
        "    description=\"Enter some text to see if it's likely fake news. \\n\"\n",
        "                \"Output includes classification, score (higher indicates fake), \"\n",
        "                \"and confidence level. \\n\",\n",
        "    elem_id=\"fake-news-detector\",\n",
        ")\n",
        "\n",
        "interface.launch()\n"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "GSSOC",
      "language": "python",
      "name": "gssoc"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.12.0"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}