Emo00-LSTM1.ipynb

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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import os\n",
    "import sys\n",
    "\n",
    "# librosa is a Python library for analyzing audio and music. It can be used to extract the data from the audio files we will see it later.\n",
    "import librosa\n",
    "import librosa.display\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
    "from sklearn.metrics import confusion_matrix, classification_report\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# to play the audio files\n",
    "from IPython.display import Audio\n",
    "\n",
    "import keras\n",
    "from keras.callbacks import ReduceLROnPlateau\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Conv1D, MaxPooling1D, Flatten, Dropout, BatchNormalization\n",
    "from keras.utils import np_utils, to_categorical\n",
    "from keras.callbacks import ModelCheckpoint\n",
    "\n",
    "import warnings\n",
    "if not sys.warnoptions:\n",
    "    warnings.simplefilter(\"ignore\")\n",
    "warnings.filterwarnings(\"ignore\", category=DeprecationWarning)\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, LSTM, Dropout, GRU, Bidirectional\n",
    "from keras.optimizers import SGD\n",
    "import math\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "957cbb4f",
   "metadata": {},
   "source": [
    "# Ravdess"
   ]
  },
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   "source": [
    "Ravdess=\"C:\\\\Users\\\\Nada Najari\\\\Downloads\\\\Ravdess\\\\audio_speech_actors_01-24\\\\\"\n",
    "ravdess_directory_list = os.listdir(Ravdess)"
   ]
  },
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Emotions</th>\n",
       "      <th>Path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>calm</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "  Emotions                                               Path\n",
       "0  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "1  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "2  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "3  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "4     calm  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s..."
      ]
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   "source": [
    "\n",
    "file_emotion = []\n",
    "file_path = []\n",
    "for dir in ravdess_directory_list:\n",
    "    # as their are 20 different actors in our previous directory we need to extract files for each actor.\n",
    "    actor = os.listdir(Ravdess + dir)\n",
    "    for file in actor:\n",
    "        part = file.split('.')[0]\n",
    "        part = part.split('-')\n",
    "        # third part in each file represents the emotion associated to that file.\n",
    "        file_emotion.append(int(part[2]))\n",
    "        file_path.append(Ravdess + dir + '/' + file)\n",
    "        \n",
    "# dataframe for emotion of files\n",
    "emotion_df = pd.DataFrame(file_emotion, columns=['Emotions'])\n",
    "\n",
    "# dataframe for path of files.\n",
    "path_df = pd.DataFrame(file_path, columns=['Path'])\n",
    "Ravdess_df = pd.concat([emotion_df, path_df], axis=1)\n",
    "\n",
    "# changing integers to actual emotions.\n",
    "Ravdess_df.Emotions.replace({1:'neutral', 2:'calm', 3:'happy', 4:'sad', 5:'angry', 6:'fear', 7:'disgust', 8:'surprise'}, inplace=True)\n",
    "Ravdess_df.head()"
   ]
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    "emotion='fear'\n",
    "path = np.array(Ravdess_df.Path[Ravdess_df.Emotions==emotion])[1]\n",
    "data, sampling_rate = librosa.load(path)"
   ]
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type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Audio(path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c03f5bb7",
   "metadata": {},
   "source": [
    "# Tess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "163c4e08",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tess=\"C:\\\\Users\\\\Nada Najari\\\\Downloads\\\\TESS\\\\tess toronto emotional speech set data/TESS Toronto emotional speech set data\\\\\"\n",
    "tess_directory_list = os.listdir(Tess)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "73a38114",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Emotions</th>\n",
       "      <th>Path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Emotions                                               Path\n",
       "0    angry  C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...\n",
       "1    angry  C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...\n",
       "2    angry  C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...\n",
       "3    angry  C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron...\n",
       "4    angry  C:\\Users\\Nada Najari\\Downloads\\TESS\\tess toron..."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_emotion = []\n",
    "file_path = []\n",
    "\n",
    "for dir in tess_directory_list:\n",
    "    directories = os.listdir(Tess + dir)\n",
    "    for file in directories:\n",
    "        part = file.split('.')[0]\n",
    "        part = part.split('_')[2]\n",
    "        if part=='ps':\n",
    "            file_emotion.append('surprise')\n",
    "        else:\n",
    "            file_emotion.append(part)\n",
    "        file_path.append(Tess + dir + '/' + file)\n",
    "# dataframe for emotion of files\n",
    "emotion_df = pd.DataFrame(file_emotion, columns=['Emotions'])\n",
    "\n",
    "# dataframe for path of files.\n",
    "path_df = pd.DataFrame(file_path, columns=['Path'])\n",
    "Tess_df = pd.concat([emotion_df, path_df], axis=1)\n",
    "Tess_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0875078f",
   "metadata": {},
   "source": [
    "# Savee"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "67b9ae9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "Savee1 = \"C:\\\\Users\\\\Nada Najari\\\\Downloads\\\\SAVEE/AudioData/DC/\"\n",
    "Savee2 = \"C:\\\\Users\\\\Nada Najari\\\\Downloads\\\\SAVEE/AudioData/JE/\"\n",
    "Savee3 = \"C:\\\\Users\\\\Nada Najari\\\\Downloads\\\\SAVEE/AudioData/JK/\"\n",
    "Savee4 = \"C:\\\\Users\\\\Nada Najari\\\\Downloads\\\\SAVEE/AudioData/KL/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "175725b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Emotions</th>\n",
       "      <th>Path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Emotions                                               Path\n",
       "0    angry  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "1    angry  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "2    angry  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "3    angry  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "4    angry  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L=[Savee1,Savee2,Savee3,Savee4]\n",
    "file_emotion=[]\n",
    "file_path=[]\n",
    "\n",
    "for i in L:\n",
    "    savee_directory_list= os.listdir(i)\n",
    "    \n",
    "    for file in savee_directory_list:\n",
    "        file_path.append(i+file)\n",
    "        ele=file[:-6]\n",
    "        if ele=='a':\n",
    "            file_emotion.append('angry')\n",
    "        elif ele=='d':\n",
    "            file_emotion.append('disgust')\n",
    "        elif ele=='f':\n",
    "            file_emotion.append('fear')\n",
    "        elif ele=='h':\n",
    "            file_emotion.append('happy')\n",
    "        elif ele=='n':\n",
    "            file_emotion.append('neutral')\n",
    "        elif ele=='sa':\n",
    "            file_emotion.append('sad')\n",
    "        else:\n",
    "            file_emotion.append('surprise')\n",
    "            \n",
    "# dataframe for emotion of files\n",
    "emotion_df = pd.DataFrame(file_emotion, columns=['Emotions'])\n",
    "\n",
    "# dataframe for path of files.\n",
    "path_df = pd.DataFrame(file_path, columns=['Path'])\n",
    "Savee_df = pd.concat([emotion_df, path_df], axis=1)\n",
    "Savee_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9899fc52",
   "metadata": {},
   "source": [
    "# Crema"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d4eecacc",
   "metadata": {},
   "outputs": [],
   "source": [
    "Crema=\"C:\\\\Users\\\\Nada Najari\\\\Downloads\\\\Crema\\\\AudioWAV\\\\\"\n",
    "crema_directory_list = os.listdir(Crema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d6b2ee1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Emotions</th>\n",
       "      <th>Path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>angry</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>disgust</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fear</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>happy</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Emotions                                               Path\n",
       "0    angry  C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...\n",
       "1  disgust  C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...\n",
       "2     fear  C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...\n",
       "3    happy  C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\...\n",
       "4  neutral  C:\\Users\\Nada Najari\\Downloads\\Crema\\AudioWAV\\..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_emotion = []\n",
    "file_path = []\n",
    "\n",
    "for file in crema_directory_list:\n",
    "    # storing file paths\n",
    "    file_path.append(Crema + file)\n",
    "    # storing file emotions\n",
    "    part=file.split('_')\n",
    "    if part[2] == 'SAD':\n",
    "        file_emotion.append('sad')\n",
    "    elif part[2] == 'ANG':\n",
    "        file_emotion.append('angry')\n",
    "    elif part[2] == 'DIS':\n",
    "        file_emotion.append('disgust')\n",
    "    elif part[2] == 'FEA':\n",
    "        file_emotion.append('fear')\n",
    "    elif part[2] == 'HAP':\n",
    "        file_emotion.append('happy')\n",
    "    elif part[2] == 'NEU':\n",
    "        file_emotion.append('neutral')\n",
    "    else:\n",
    "        file_emotion.append('Unknown')\n",
    "        \n",
    "# dataframe for emotion of files\n",
    "emotion_df = pd.DataFrame(file_emotion, columns=['Emotions'])\n",
    "\n",
    "# dataframe for path of files.\n",
    "path_df = pd.DataFrame(file_path, columns=['Path'])\n",
    "Crema_df = pd.concat([emotion_df, path_df], axis=1)\n",
    "Crema_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc2d23a3",
   "metadata": {},
   "source": [
    "# Final Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "25b26015",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Emotions</th>\n",
       "      <th>Path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>calm</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Emotions                                               Path\n",
       "0  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "1  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "2  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "3  neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "4     calm  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s..."
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# creating Dataframe using all the 4 dataframes we created so far.\n",
    "data_path = pd.concat([Ravdess_df, Crema_df, Tess_df, Savee_df], axis = 0)\n",
    "data_path.to_csv(\"data_path.csv\",index=False)\n",
    "data_path.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7306c6a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Emotions</th>\n",
       "      <th>Path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>calm</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12162 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Emotions                                               Path\n",
       "0     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "1     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "2     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "3     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "4        calm  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "..        ...                                                ...\n",
       "475  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "476  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "477  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "478  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "479  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "\n",
       "[12162 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fcebbf58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Emotions</th>\n",
       "      <th>Path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>neutral</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>calm</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12157</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12158</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12159</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12160</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12161</th>\n",
       "      <td>surprise</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12162 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Emotions                                               Path\n",
       "0       neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "1       neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "2       neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "3       neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "4          calm  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "...         ...                                                ...\n",
       "12157  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "12158  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "12159  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "12160  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "12161  surprise  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "\n",
       "[12162 rows x 2 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_path.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2de322db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['neutral', 'calm', 'happy', 'sad', 'angry', 'fear', 'disgust',\n",
       "       'surprise'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_path['Emotions'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0136ede4",
   "metadata": {},
   "source": [
    "# Visualisation des données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4eb89e30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_path['Emotions'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e6ec2821",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'neutral': 1703,\n",
       "         'calm': 192,\n",
       "         'happy': 1923,\n",
       "         'sad': 1923,\n",
       "         'angry': 1923,\n",
       "         'fear': 1923,\n",
       "         'disgust': 1923,\n",
       "         'surprise': 652})"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import collections\n",
    "collections.Counter(data_path['Emotions'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9868f610",
   "metadata": {},
   "source": [
    "# Final Classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "358f8fed",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.concat([data_path.loc[data_path['Emotions']=='neutral'], data_path.loc[data_path['Emotions']=='sad'], data_path.loc[data_path['Emotions']=='angry'],data_path.loc[data_path['Emotions']=='fear'], data_path.loc[data_path['Emotions']=='disgust']], axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "84a7f27d",
   "metadata": {},
   "outputs": [
    {
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       "      <th>386</th>\n",
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       "    <tr>\n",
       "      <th>387</th>\n",
       "      <td>disgust</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
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       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>disgust</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>disgust</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9395 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Emotions                                               Path\n",
       "0    neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "1    neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "2    neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "3    neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "60   neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "..       ...                                                ...\n",
       "385  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "386  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "387  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "388  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "389  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "\n",
       "[9395 rows x 2 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ad33017d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>disgust</td>\n",
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       "      <th>9391</th>\n",
       "      <td>disgust</td>\n",
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       "      <th>9392</th>\n",
       "      <td>disgust</td>\n",
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       "    <tr>\n",
       "      <th>9393</th>\n",
       "      <td>disgust</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
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       "    <tr>\n",
       "      <th>9394</th>\n",
       "      <td>disgust</td>\n",
       "      <td>C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9395 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Emotions                                               Path\n",
       "0     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "1     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "2     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "3     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "4     neutral  C:\\Users\\Nada Najari\\Downloads\\Ravdess\\audio_s...\n",
       "...       ...                                                ...\n",
       "9390  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "9391  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "9392  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "9393  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "9394  disgust  C:\\Users\\Nada Najari\\Downloads\\SAVEE/AudioData...\n",
       "\n",
       "[9395 rows x 2 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "40b6d2bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['neutral', 'sad', 'angry', 'fear', 'disgust'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Emotions'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6b510833",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=pd.read_csv('Final Dataset2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "eea328d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.drop(df1.filter(regex='Unname'),axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9c53ac86",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <td>-6.675679</td>\n",
       "      <td>-24.009238</td>\n",
       "      <td>-21.898692</td>\n",
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       "      <td>-0.299692</td>\n",
       "      <td>-0.469536</td>\n",
       "      <td>-0.242703</td>\n",
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       "      <td>-0.447229</td>\n",
       "      <td>1.308129</td>\n",
       "      <td>-0.901984</td>\n",
       "      <td>0.074005</td>\n",
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       "      <td>-3.205864</td>\n",
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       "      <td>10.404853</td>\n",
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       "      <td>8.596527</td>\n",
       "      <td>-16.117351</td>\n",
       "      <td>-27.187871</td>\n",
       "      <td>-18.708665</td>\n",
       "      <td>...</td>\n",
       "      <td>0.687796</td>\n",
       "      <td>0.420799</td>\n",
       "      <td>-0.233304</td>\n",
       "      <td>0.202395</td>\n",
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       "      <td>0.792490</td>\n",
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       "      <td>-3.469831</td>\n",
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       "      <td>1.797657</td>\n",
       "      <td>-20.784271</td>\n",
       "      <td>42.352236</td>\n",
       "      <td>-4.013058</td>\n",
       "      <td>-26.243642</td>\n",
       "      <td>-25.549737</td>\n",
       "      <td>-8.902485</td>\n",
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       "      <td>0.864846</td>\n",
       "      <td>-0.627041</td>\n",
       "      <td>0.592732</td>\n",
       "      <td>0.334145</td>\n",
       "      <td>-0.403551</td>\n",
       "      <td>-0.301404</td>\n",
       "      <td>0.074032</td>\n",
       "      <td>-0.474449</td>\n",
       "      <td>-0.136121</td>\n",
       "      <td>-0.188187</td>\n",
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       "      <td>38.011624</td>\n",
       "      <td>-45.106124</td>\n",
       "      <td>17.291470</td>\n",
       "      <td>24.274299</td>\n",
       "      <td>16.911050</td>\n",
       "      <td>-1.818234</td>\n",
       "      <td>-10.210623</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.033271</td>\n",
       "      <td>-0.323766</td>\n",
       "      <td>-0.604076</td>\n",
       "      <td>0.161224</td>\n",
       "      <td>0.557430</td>\n",
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       "      <td>0.043716</td>\n",
       "      <td>-0.114555</td>\n",
       "      <td>1.162881</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>-2.945932</td>\n",
       "      <td>3.725810</td>\n",
       "      <td>-12.112875</td>\n",
       "      <td>7.264827</td>\n",
       "      <td>-15.795024</td>\n",
       "      <td>25.881972</td>\n",
       "      <td>-19.275158</td>\n",
       "      <td>-7.587172</td>\n",
       "      <td>22.424130</td>\n",
       "      <td>...</td>\n",
       "      <td>1.517529</td>\n",
       "      <td>0.800184</td>\n",
       "      <td>1.778371</td>\n",
       "      <td>0.308376</td>\n",
       "      <td>-0.359344</td>\n",
       "      <td>-0.000718</td>\n",
       "      <td>1.132752</td>\n",
       "      <td>4.230298</td>\n",
       "      <td>2.483101</td>\n",
       "      <td>2.587484</td>\n",
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       "      <th>12158</th>\n",
       "      <td>0.053261</td>\n",
       "      <td>-4.919584</td>\n",
       "      <td>-2.120354</td>\n",
       "      <td>82.102786</td>\n",
       "      <td>-18.546229</td>\n",
       "      <td>-42.842034</td>\n",
       "      <td>-21.617220</td>\n",
       "      <td>8.952767</td>\n",
       "      <td>20.462003</td>\n",
       "      <td>31.048866</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.225771</td>\n",
       "      <td>-0.772897</td>\n",
       "      <td>0.972035</td>\n",
       "      <td>-0.944760</td>\n",
       "      <td>-0.599139</td>\n",
       "      <td>2.645078</td>\n",
       "      <td>-1.683720</td>\n",
       "      <td>-0.398122</td>\n",
       "      <td>0.328068</td>\n",
       "      <td>-0.035153</td>\n",
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       "      <th>12159</th>\n",
       "      <td>0.108217</td>\n",
       "      <td>-3.705113</td>\n",
       "      <td>5.056894</td>\n",
       "      <td>41.105760</td>\n",
       "      <td>-53.075460</td>\n",
       "      <td>24.179237</td>\n",
       "      <td>27.969192</td>\n",
       "      <td>18.775622</td>\n",
       "      <td>-5.020289</td>\n",
       "      <td>-13.963065</td>\n",
       "      <td>...</td>\n",
       "      <td>1.121093</td>\n",
       "      <td>0.242182</td>\n",
       "      <td>0.212024</td>\n",
       "      <td>0.060927</td>\n",
       "      <td>-0.715895</td>\n",
       "      <td>0.321182</td>\n",
       "      <td>1.896841</td>\n",
       "      <td>0.181938</td>\n",
       "      <td>-1.823358</td>\n",
       "      <td>-0.580570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12160</th>\n",
       "      <td>-13.780785</td>\n",
       "      <td>242.648368</td>\n",
       "      <td>-352.340316</td>\n",
       "      <td>-109.102241</td>\n",
       "      <td>-165.478393</td>\n",
       "      <td>-67.795003</td>\n",
       "      <td>-29.006885</td>\n",
       "      <td>0.240993</td>\n",
       "      <td>17.954897</td>\n",
       "      <td>33.955320</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.207121</td>\n",
       "      <td>2.894432</td>\n",
       "      <td>0.671065</td>\n",
       "      <td>2.698027</td>\n",
       "      <td>0.736062</td>\n",
       "      <td>-2.474920</td>\n",
       "      <td>2.501873</td>\n",
       "      <td>-3.023414</td>\n",
       "      <td>-0.773438</td>\n",
       "      <td>2.264807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12161</th>\n",
       "      <td>-35.730088</td>\n",
       "      <td>638.186548</td>\n",
       "      <td>158.106224</td>\n",
       "      <td>29.491793</td>\n",
       "      <td>7.557288</td>\n",
       "      <td>-26.080701</td>\n",
       "      <td>-40.276602</td>\n",
       "      <td>-42.373951</td>\n",
       "      <td>-51.211405</td>\n",
       "      <td>-65.719004</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.894789</td>\n",
       "      <td>-0.463832</td>\n",
       "      <td>-0.516002</td>\n",
       "      <td>0.805588</td>\n",
       "      <td>-1.389722</td>\n",
       "      <td>0.358453</td>\n",
       "      <td>-1.296050</td>\n",
       "      <td>-0.136555</td>\n",
       "      <td>-0.282579</td>\n",
       "      <td>-1.024499</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12162 rows × 800 columns</p>\n",
       "</div>"
      ],
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       "              x0          x1          x2          x3          x4         x5  \\\n",
       "0      -1.979558   -3.021072    4.157546   15.732176  -34.424443  39.654388   \n",
       "1      -1.849681   -3.118820    4.358643   18.432433  -36.721770  38.320672   \n",
       "2      -1.780895   -3.205864    3.835181   10.404853  -29.710821  41.403476   \n",
       "3      -1.408252   -3.469831    3.233724    1.797657  -20.784271  42.352236   \n",
       "4      -2.058326   -3.518295    4.416538   38.011624  -45.106124  17.291470   \n",
       "...          ...         ...         ...         ...         ...        ...   \n",
       "12157  -0.748382   -2.945932    3.725810  -12.112875    7.264827 -15.795024   \n",
       "12158   0.053261   -4.919584   -2.120354   82.102786  -18.546229 -42.842034   \n",
       "12159   0.108217   -3.705113    5.056894   41.105760  -53.075460  24.179237   \n",
       "12160 -13.780785  242.648368 -352.340316 -109.102241 -165.478393 -67.795003   \n",
       "12161 -35.730088  638.186548  158.106224   29.491793    7.557288 -26.080701   \n",
       "\n",
       "              x6         x7         x8         x9  ...      x790      x791  \\\n",
       "0      14.705246  -9.764299 -25.450203 -21.552517  ...  0.560407  0.253715   \n",
       "1      16.887618  -6.675679 -24.009238 -21.898692  ... -0.299692 -0.469536   \n",
       "2       8.596527 -16.117351 -27.187871 -18.708665  ...  0.687796  0.420799   \n",
       "3      -4.013058 -26.243642 -25.549737  -8.902485  ...  0.864846 -0.627041   \n",
       "4      24.274299  16.911050  -1.818234 -10.210623  ... -1.033271 -0.323766   \n",
       "...          ...        ...        ...        ...  ...       ...       ...   \n",
       "12157  25.881972 -19.275158  -7.587172  22.424130  ...  1.517529  0.800184   \n",
       "12158 -21.617220   8.952767  20.462003  31.048866  ... -2.225771 -0.772897   \n",
       "12159  27.969192  18.775622  -5.020289 -13.963065  ...  1.121093  0.242182   \n",
       "12160 -29.006885   0.240993  17.954897  33.955320  ... -1.207121  2.894432   \n",
       "12161 -40.276602 -42.373951 -51.211405 -65.719004  ... -0.894789 -0.463832   \n",
       "\n",
       "           x792      x793      x794      x795      x796      x797      x798  \\\n",
       "0      0.138367 -0.533811 -0.169403  0.669081  0.888801  1.399485  0.743607   \n",
       "1     -0.242703  0.355703  0.255354 -0.447229  1.308129 -0.901984  0.074005   \n",
       "2     -0.233304  0.202395  0.998187  0.792490 -0.201708  1.004649 -0.522653   \n",
       "3      0.592732  0.334145 -0.403551 -0.301404  0.074032 -0.474449 -0.136121   \n",
       "4     -0.604076  0.161224  0.557430  0.704192  0.043716 -0.114555  1.162881   \n",
       "...         ...       ...       ...       ...       ...       ...       ...   \n",
       "12157  1.778371  0.308376 -0.359344 -0.000718  1.132752  4.230298  2.483101   \n",
       "12158  0.972035 -0.944760 -0.599139  2.645078 -1.683720 -0.398122  0.328068   \n",
       "12159  0.212024  0.060927 -0.715895  0.321182  1.896841  0.181938 -1.823358   \n",
       "12160  0.671065  2.698027  0.736062 -2.474920  2.501873 -3.023414 -0.773438   \n",
       "12161 -0.516002  0.805588 -1.389722  0.358453 -1.296050 -0.136555 -0.282579   \n",
       "\n",
       "           x799  \n",
       "0     -0.720082  \n",
       "1      0.867657  \n",
       "2     -0.381420  \n",
       "3     -0.188187  \n",
       "4      0.280118  \n",
       "...         ...  \n",
       "12157  2.587484  \n",
       "12158 -0.035153  \n",
       "12159 -0.580570  \n",
       "12160  2.264807  \n",
       "12161 -1.024499  \n",
       "\n",
       "[12162 rows x 800 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d1df14e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "L=list(zip(data_path.Path, data_path.Emotions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "64355634",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12162"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0b827847",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x0</th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>x4</th>\n",
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       "      <th>x793</th>\n",
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       "      <th>x797</th>\n",
       "      <th>x798</th>\n",
       "      <th>x799</th>\n",
       "      <th>emotions</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1.979558</td>\n",
       "      <td>-3.021072</td>\n",
       "      <td>4.157546</td>\n",
       "      <td>15.732176</td>\n",
       "      <td>-34.424443</td>\n",
       "      <td>39.654388</td>\n",
       "      <td>14.705246</td>\n",
       "      <td>-9.764299</td>\n",
       "      <td>-25.450203</td>\n",
       "      <td>-21.552517</td>\n",
       "      <td>...</td>\n",
       "      <td>0.253715</td>\n",
       "      <td>0.138367</td>\n",
       "      <td>-0.533811</td>\n",
       "      <td>-0.169403</td>\n",
       "      <td>0.669081</td>\n",
       "      <td>0.888801</td>\n",
       "      <td>1.399485</td>\n",
       "      <td>0.743607</td>\n",
       "      <td>-0.720082</td>\n",
       "      <td>neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.849681</td>\n",
       "      <td>-3.118820</td>\n",
       "      <td>4.358643</td>\n",
       "      <td>18.432433</td>\n",
       "      <td>-36.721770</td>\n",
       "      <td>38.320672</td>\n",
       "      <td>16.887618</td>\n",
       "      <td>-6.675679</td>\n",
       "      <td>-24.009238</td>\n",
       "      <td>-21.898692</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.469536</td>\n",
       "      <td>-0.242703</td>\n",
       "      <td>0.355703</td>\n",
       "      <td>0.255354</td>\n",
       "      <td>-0.447229</td>\n",
       "      <td>1.308129</td>\n",
       "      <td>-0.901984</td>\n",
       "      <td>0.074005</td>\n",
       "      <td>0.867657</td>\n",
       "      <td>neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.780895</td>\n",
       "      <td>-3.205864</td>\n",
       "      <td>3.835181</td>\n",
       "      <td>10.404853</td>\n",
       "      <td>-29.710821</td>\n",
       "      <td>41.403476</td>\n",
       "      <td>8.596527</td>\n",
       "      <td>-16.117351</td>\n",
       "      <td>-27.187871</td>\n",
       "      <td>-18.708665</td>\n",
       "      <td>...</td>\n",
       "      <td>0.420799</td>\n",
       "      <td>-0.233304</td>\n",
       "      <td>0.202395</td>\n",
       "      <td>0.998187</td>\n",
       "      <td>0.792490</td>\n",
       "      <td>-0.201708</td>\n",
       "      <td>1.004649</td>\n",
       "      <td>-0.522653</td>\n",
       "      <td>-0.381420</td>\n",
       "      <td>neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.408252</td>\n",
       "      <td>-3.469831</td>\n",
       "      <td>3.233724</td>\n",
       "      <td>1.797657</td>\n",
       "      <td>-20.784271</td>\n",
       "      <td>42.352236</td>\n",
       "      <td>-4.013058</td>\n",
       "      <td>-26.243642</td>\n",
       "      <td>-25.549737</td>\n",
       "      <td>-8.902485</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.627041</td>\n",
       "      <td>0.592732</td>\n",
       "      <td>0.334145</td>\n",
       "      <td>-0.403551</td>\n",
       "      <td>-0.301404</td>\n",
       "      <td>0.074032</td>\n",
       "      <td>-0.474449</td>\n",
       "      <td>-0.136121</td>\n",
       "      <td>-0.188187</td>\n",
       "      <td>neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.799636</td>\n",
       "      <td>-3.267139</td>\n",
       "      <td>2.679379</td>\n",
       "      <td>52.727960</td>\n",
       "      <td>-49.387958</td>\n",
       "      <td>5.418391</td>\n",
       "      <td>21.012070</td>\n",
       "      <td>24.241493</td>\n",
       "      <td>10.775952</td>\n",
       "      <td>1.493472</td>\n",
       "      <td>...</td>\n",
       "      <td>0.041254</td>\n",
       "      <td>-2.690339</td>\n",
       "      <td>1.080970</td>\n",
       "      <td>1.472156</td>\n",
       "      <td>-1.274416</td>\n",
       "      <td>-1.485488</td>\n",
       "      <td>-0.258286</td>\n",
       "      <td>0.174817</td>\n",
       "      <td>-2.607576</td>\n",
       "      <td>neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9390</th>\n",
       "      <td>-1.459302</td>\n",
       "      <td>-3.010511</td>\n",
       "      <td>4.118166</td>\n",
       "      <td>-0.010781</td>\n",
       "      <td>-20.978018</td>\n",
       "      <td>48.195636</td>\n",
       "      <td>-6.677730</td>\n",
       "      <td>-30.065707</td>\n",
       "      <td>-28.280893</td>\n",
       "      <td>-8.163405</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.193725</td>\n",
       "      <td>0.550442</td>\n",
       "      <td>-0.666402</td>\n",
       "      <td>-0.197189</td>\n",
       "      <td>-0.054020</td>\n",
       "      <td>0.117039</td>\n",
       "      <td>-0.569047</td>\n",
       "      <td>1.130773</td>\n",
       "      <td>0.681678</td>\n",
       "      <td>disgust</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9391</th>\n",
       "      <td>-0.634904</td>\n",
       "      <td>-3.505377</td>\n",
       "      <td>4.212638</td>\n",
       "      <td>-15.635285</td>\n",
       "      <td>9.163616</td>\n",
       "      <td>-14.395509</td>\n",
       "      <td>5.007299</td>\n",
       "      <td>24.489789</td>\n",
       "      <td>-20.599147</td>\n",
       "      <td>-10.863483</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.270261</td>\n",
       "      <td>-0.298726</td>\n",
       "      <td>0.157748</td>\n",
       "      <td>-0.247462</td>\n",
       "      <td>0.266724</td>\n",
       "      <td>0.807128</td>\n",
       "      <td>0.013425</td>\n",
       "      <td>-0.534945</td>\n",
       "      <td>0.800395</td>\n",
       "      <td>disgust</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9392</th>\n",
       "      <td>0.908243</td>\n",
       "      <td>-2.223109</td>\n",
       "      <td>-70.365636</td>\n",
       "      <td>104.615107</td>\n",
       "      <td>120.949184</td>\n",
       "      <td>-4.037948</td>\n",
       "      <td>-40.298906</td>\n",
       "      <td>-47.308175</td>\n",
       "      <td>-55.959758</td>\n",
       "      <td>-51.326461</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.697541</td>\n",
       "      <td>-0.422377</td>\n",
       "      <td>-1.426053</td>\n",
       "      <td>3.131066</td>\n",
       "      <td>0.365983</td>\n",
       "      <td>-2.992455</td>\n",
       "      <td>-0.610183</td>\n",
       "      <td>-2.000497</td>\n",
       "      <td>1.737954</td>\n",
       "      <td>disgust</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9393</th>\n",
       "      <td>0.144398</td>\n",
       "      <td>5.509049</td>\n",
       "      <td>-132.056498</td>\n",
       "      <td>90.884228</td>\n",
       "      <td>155.150308</td>\n",
       "      <td>59.087185</td>\n",
       "      <td>10.675664</td>\n",
       "      <td>-13.897746</td>\n",
       "      <td>-38.863476</td>\n",
       "      <td>-48.106556</td>\n",
       "      <td>...</td>\n",
       "      <td>1.237215</td>\n",
       "      <td>-0.616922</td>\n",
       "      <td>-0.708622</td>\n",
       "      <td>-0.202181</td>\n",
       "      <td>-0.224961</td>\n",
       "      <td>-0.579425</td>\n",
       "      <td>0.578058</td>\n",
       "      <td>-1.538056</td>\n",
       "      <td>1.327839</td>\n",
       "      <td>disgust</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9394</th>\n",
       "      <td>-16.014014</td>\n",
       "      <td>276.267726</td>\n",
       "      <td>-329.619103</td>\n",
       "      <td>-117.296914</td>\n",
       "      <td>-196.436108</td>\n",
       "      <td>-104.247009</td>\n",
       "      <td>-60.873060</td>\n",
       "      <td>-25.503247</td>\n",
       "      <td>-5.113459</td>\n",
       "      <td>11.787239</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.708995</td>\n",
       "      <td>-0.914200</td>\n",
       "      <td>0.985054</td>\n",
       "      <td>3.092364</td>\n",
       "      <td>-1.119678</td>\n",
       "      <td>2.624522</td>\n",
       "      <td>1.336081</td>\n",
       "      <td>0.424619</td>\n",
       "      <td>0.638918</td>\n",
       "      <td>disgust</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9395 rows × 801 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             x0          x1          x2          x3          x4          x5  \\\n",
       "0     -1.979558   -3.021072    4.157546   15.732176  -34.424443   39.654388   \n",
       "1     -1.849681   -3.118820    4.358643   18.432433  -36.721770   38.320672   \n",
       "2     -1.780895   -3.205864    3.835181   10.404853  -29.710821   41.403476   \n",
       "3     -1.408252   -3.469831    3.233724    1.797657  -20.784271   42.352236   \n",
       "4     -1.799636   -3.267139    2.679379   52.727960  -49.387958    5.418391   \n",
       "...         ...         ...         ...         ...         ...         ...   \n",
       "9390  -1.459302   -3.010511    4.118166   -0.010781  -20.978018   48.195636   \n",
       "9391  -0.634904   -3.505377    4.212638  -15.635285    9.163616  -14.395509   \n",
       "9392   0.908243   -2.223109  -70.365636  104.615107  120.949184   -4.037948   \n",
       "9393   0.144398    5.509049 -132.056498   90.884228  155.150308   59.087185   \n",
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       "             x6         x7         x8         x9  ...      x791      x792  \\\n",
       "0     14.705246  -9.764299 -25.450203 -21.552517  ...  0.253715  0.138367   \n",
       "1     16.887618  -6.675679 -24.009238 -21.898692  ... -0.469536 -0.242703   \n",
       "2      8.596527 -16.117351 -27.187871 -18.708665  ...  0.420799 -0.233304   \n",
       "3     -4.013058 -26.243642 -25.549737  -8.902485  ... -0.627041  0.592732   \n",
       "4     21.012070  24.241493  10.775952   1.493472  ...  0.041254 -2.690339   \n",
       "...         ...        ...        ...        ...  ...       ...       ...   \n",
       "9390  -6.677730 -30.065707 -28.280893  -8.163405  ... -0.193725  0.550442   \n",
       "9391   5.007299  24.489789 -20.599147 -10.863483  ... -0.270261 -0.298726   \n",
       "9392 -40.298906 -47.308175 -55.959758 -51.326461  ... -1.697541 -0.422377   \n",
       "9393  10.675664 -13.897746 -38.863476 -48.106556  ...  1.237215 -0.616922   \n",
       "9394 -60.873060 -25.503247  -5.113459  11.787239  ... -0.708995 -0.914200   \n",
       "\n",
       "          x793      x794      x795      x796      x797      x798      x799  \\\n",
       "0    -0.533811 -0.169403  0.669081  0.888801  1.399485  0.743607 -0.720082   \n",
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       "2     0.202395  0.998187  0.792490 -0.201708  1.004649 -0.522653 -0.381420   \n",
       "3     0.334145 -0.403551 -0.301404  0.074032 -0.474449 -0.136121 -0.188187   \n",
       "4     1.080970  1.472156 -1.274416 -1.485488 -0.258286  0.174817 -2.607576   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
       "9390 -0.666402 -0.197189 -0.054020  0.117039 -0.569047  1.130773  0.681678   \n",
       "9391  0.157748 -0.247462  0.266724  0.807128  0.013425 -0.534945  0.800395   \n",
       "9392 -1.426053  3.131066  0.365983 -2.992455 -0.610183 -2.000497  1.737954   \n",
       "9393 -0.708622 -0.202181 -0.224961 -0.579425  0.578058 -1.538056  1.327839   \n",
       "9394  0.985054  3.092364 -1.119678  2.624522  1.336081  0.424619  0.638918   \n",
       "\n",
       "      emotions  \n",
       "0      neutral  \n",
       "1      neutral  \n",
       "2      neutral  \n",
       "3      neutral  \n",
       "4      neutral  \n",
       "...        ...  \n",
       "9390   disgust  \n",
       "9391   disgust  \n",
       "9392   disgust  \n",
       "9393   disgust  \n",
       "9394   disgust  \n",
       "\n",
       "[9395 rows x 801 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L=list(zip(data_path.Path, data_path.Emotions))\n",
    "\n",
    "\n",
    "\n",
    "emotions=[]\n",
    "for i in L:\n",
    "    emotions.append(i[1])\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "df1['emotions']=emotions\n",
    "\n",
    "\n",
    "\n",
    "df1=pd.concat([df1.loc[df1['emotions']=='neutral'], df1.loc[df1['emotions']=='sad'], df1.loc[df1['emotions']=='angry'],df1.loc[df1['emotions']=='fear'], df1.loc[df1['emotions']=='disgust']], axis = 0)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "df1.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2e366732",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['neutral', 'sad', 'angry', 'fear', 'disgust'], dtype=object)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['emotions'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7c252c0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(df1, df1['emotions'], test_size = 0.3, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a5be7271",
   "metadata": {},
   "outputs": [],
   "source": [
    "m=[0,1,2,3,4]\n",
    "emo=['neutral', 'sad', 'angry', 'fear', 'disgust']\n",
    "df=df1.replace(emo,m)\n",
    "df=df.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "74889902",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>x0</th>\n",
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       "      <td>-1.849681</td>\n",
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       "      <td>-36.721770</td>\n",
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       "      <td>10.404853</td>\n",
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       "      <td>-27.187871</td>\n",
       "      <td>-18.708665</td>\n",
       "      <td>...</td>\n",
       "      <td>0.420799</td>\n",
       "      <td>-0.233304</td>\n",
       "      <td>0.202395</td>\n",
       "      <td>0.998187</td>\n",
       "      <td>0.792490</td>\n",
       "      <td>-0.201708</td>\n",
       "      <td>1.004649</td>\n",
       "      <td>-0.522653</td>\n",
       "      <td>-0.381420</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.408252</td>\n",
       "      <td>-3.469831</td>\n",
       "      <td>3.233724</td>\n",
       "      <td>1.797657</td>\n",
       "      <td>-20.784271</td>\n",
       "      <td>42.352236</td>\n",
       "      <td>-4.013058</td>\n",
       "      <td>-26.243642</td>\n",
       "      <td>-25.549737</td>\n",
       "      <td>-8.902485</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.627041</td>\n",
       "      <td>0.592732</td>\n",
       "      <td>0.334145</td>\n",
       "      <td>-0.403551</td>\n",
       "      <td>-0.301404</td>\n",
       "      <td>0.074032</td>\n",
       "      <td>-0.474449</td>\n",
       "      <td>-0.136121</td>\n",
       "      <td>-0.188187</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>-1.799636</td>\n",
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       "      <td>-49.387958</td>\n",
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       "      <td>21.012070</td>\n",
       "      <td>24.241493</td>\n",
       "      <td>10.775952</td>\n",
       "      <td>1.493472</td>\n",
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       "      <td>0.041254</td>\n",
       "      <td>-2.690339</td>\n",
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       "      <td>0.174817</td>\n",
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       "      <th>9390</th>\n",
       "      <td>-1.459302</td>\n",
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       "      <td>-30.065707</td>\n",
       "      <td>-28.280893</td>\n",
       "      <td>-8.163405</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.193725</td>\n",
       "      <td>0.550442</td>\n",
       "      <td>-0.666402</td>\n",
       "      <td>-0.197189</td>\n",
       "      <td>-0.054020</td>\n",
       "      <td>0.117039</td>\n",
       "      <td>-0.569047</td>\n",
       "      <td>1.130773</td>\n",
       "      <td>0.681678</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>9391</th>\n",
       "      <td>-0.634904</td>\n",
       "      <td>-3.505377</td>\n",
       "      <td>4.212638</td>\n",
       "      <td>-15.635285</td>\n",
       "      <td>9.163616</td>\n",
       "      <td>-14.395509</td>\n",
       "      <td>5.007299</td>\n",
       "      <td>24.489789</td>\n",
       "      <td>-20.599147</td>\n",
       "      <td>-10.863483</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.270261</td>\n",
       "      <td>-0.298726</td>\n",
       "      <td>0.157748</td>\n",
       "      <td>-0.247462</td>\n",
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       "      <td>0.013425</td>\n",
       "      <td>-0.534945</td>\n",
       "      <td>0.800395</td>\n",
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       "    <tr>\n",
       "      <th>9392</th>\n",
       "      <td>0.908243</td>\n",
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       "      <td>-70.365636</td>\n",
       "      <td>104.615107</td>\n",
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       "      <td>-4.037948</td>\n",
       "      <td>-40.298906</td>\n",
       "      <td>-47.308175</td>\n",
       "      <td>-55.959758</td>\n",
       "      <td>-51.326461</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.697541</td>\n",
       "      <td>-0.422377</td>\n",
       "      <td>-1.426053</td>\n",
       "      <td>3.131066</td>\n",
       "      <td>0.365983</td>\n",
       "      <td>-2.992455</td>\n",
       "      <td>-0.610183</td>\n",
       "      <td>-2.000497</td>\n",
       "      <td>1.737954</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>9393</th>\n",
       "      <td>0.144398</td>\n",
       "      <td>5.509049</td>\n",
       "      <td>-132.056498</td>\n",
       "      <td>90.884228</td>\n",
       "      <td>155.150308</td>\n",
       "      <td>59.087185</td>\n",
       "      <td>10.675664</td>\n",
       "      <td>-13.897746</td>\n",
       "      <td>-38.863476</td>\n",
       "      <td>-48.106556</td>\n",
       "      <td>...</td>\n",
       "      <td>1.237215</td>\n",
       "      <td>-0.616922</td>\n",
       "      <td>-0.708622</td>\n",
       "      <td>-0.202181</td>\n",
       "      <td>-0.224961</td>\n",
       "      <td>-0.579425</td>\n",
       "      <td>0.578058</td>\n",
       "      <td>-1.538056</td>\n",
       "      <td>1.327839</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>9394</th>\n",
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       "      <td>-104.247009</td>\n",
       "      <td>-60.873060</td>\n",
       "      <td>-25.503247</td>\n",
       "      <td>-5.113459</td>\n",
       "      <td>11.787239</td>\n",
       "      <td>...</td>\n",
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       "      <td>-0.914200</td>\n",
       "      <td>0.985054</td>\n",
       "      <td>3.092364</td>\n",
       "      <td>-1.119678</td>\n",
       "      <td>2.624522</td>\n",
       "      <td>1.336081</td>\n",
       "      <td>0.424619</td>\n",
       "      <td>0.638918</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9395 rows × 801 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             x0          x1          x2          x3          x4          x5  \\\n",
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       "...         ...         ...         ...         ...         ...         ...   \n",
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       "\n",
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       "\n",
       "          x793      x794      x795      x796      x797      x798      x799  \\\n",
       "0    -0.533811 -0.169403  0.669081  0.888801  1.399485  0.743607 -0.720082   \n",
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       "2     0.202395  0.998187  0.792490 -0.201708  1.004649 -0.522653 -0.381420   \n",
       "3     0.334145 -0.403551 -0.301404  0.074032 -0.474449 -0.136121 -0.188187   \n",
       "4     1.080970  1.472156 -1.274416 -1.485488 -0.258286  0.174817 -2.607576   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
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       "9394  0.985054  3.092364 -1.119678  2.624522  1.336081  0.424619  0.638918   \n",
       "\n",
       "      emotions  \n",
       "0            0  \n",
       "1            0  \n",
       "2            0  \n",
       "3            0  \n",
       "4            0  \n",
       "...        ...  \n",
       "9390         4  \n",
       "9391         4  \n",
       "9392         4  \n",
       "9393         4  \n",
       "9394         4  \n",
       "\n",
       "[9395 rows x 801 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c8bb932a",
   "metadata": {},
   "outputs": [
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       "<p>9395 rows × 800 columns</p>\n",
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       "...        ...       ...       ...       ...       ...       ...       ...   \n",
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       "\n",
       "          x799  \n",
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       "...        ...  \n",
       "9390  0.681678  \n",
       "9391  0.800395  \n",
       "9392  1.737954  \n",
       "9393  1.327839  \n",
       "9394  0.638918  \n",
       "\n",
       "[9395 rows x 800 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y=df['emotions']\n",
    "df.drop(['emotions'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5fa77d9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(df, y, test_size = 0.3, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "8f480283",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, y_train = np.array(X_train), np.array(y_train)\n",
    "X_train = np.reshape(X_train, (X_train.shape[0],X_train.shape[1],1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8443aba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = np.asarray(X_train).astype(np.int_)\n",
    "y_train = np.array(y_train).astype(np.int_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "ae247ce7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/25\n",
      "206/206 [==============================] - 152s 705ms/step - loss: 1.8912 - accuracy: 0.1977\n",
      "Epoch 2/25\n",
      "  9/206 [>.............................] - ETA: 2:22 - loss: 0.4806 - accuracy: 0.1354"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[1;32mIn [39]\u001b[0m, in \u001b[0;36m<cell line: 21>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     19\u001b[0m regressor\u001b[38;5;241m.\u001b[39mcompile(optimizer\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrmsprop\u001b[39m\u001b[38;5;124m'\u001b[39m,loss\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmean_squared_error\u001b[39m\u001b[38;5;124m'\u001b[39m,metrics\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124maccuracy\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m     20\u001b[0m \u001b[38;5;66;03m# Fitting to the training set\u001b[39;00m\n\u001b[1;32m---> 21\u001b[0m \u001b[43mregressor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43my_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m25\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m32\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\keras\\utils\\traceback_utils.py:64\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     62\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m     63\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m---> 64\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m     65\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:  \u001b[38;5;66;03m# pylint: disable=broad-except\u001b[39;00m\n\u001b[0;32m     66\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\keras\\engine\\training.py:1409\u001b[0m, in \u001b[0;36mModel.fit\u001b[1;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)\u001b[0m\n\u001b[0;32m   1402\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m tf\u001b[38;5;241m.\u001b[39mprofiler\u001b[38;5;241m.\u001b[39mexperimental\u001b[38;5;241m.\u001b[39mTrace(\n\u001b[0;32m   1403\u001b[0m     \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtrain\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m   1404\u001b[0m     epoch_num\u001b[38;5;241m=\u001b[39mepoch,\n\u001b[0;32m   1405\u001b[0m     step_num\u001b[38;5;241m=\u001b[39mstep,\n\u001b[0;32m   1406\u001b[0m     batch_size\u001b[38;5;241m=\u001b[39mbatch_size,\n\u001b[0;32m   1407\u001b[0m     _r\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m):\n\u001b[0;32m   1408\u001b[0m   callbacks\u001b[38;5;241m.\u001b[39mon_train_batch_begin(step)\n\u001b[1;32m-> 1409\u001b[0m   tmp_logs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1410\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m data_handler\u001b[38;5;241m.\u001b[39mshould_sync:\n\u001b[0;32m   1411\u001b[0m     context\u001b[38;5;241m.\u001b[39masync_wait()\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\traceback_utils.py:150\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    148\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    149\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 150\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m    151\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    152\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow\\python\\eager\\def_function.py:915\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m    912\u001b[0m compiler \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mxla\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnonXla\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    914\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m OptionalXlaContext(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile):\n\u001b[1;32m--> 915\u001b[0m   result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n\u001b[0;32m    917\u001b[0m new_tracing_count \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexperimental_get_tracing_count()\n\u001b[0;32m    918\u001b[0m without_tracing \u001b[38;5;241m=\u001b[39m (tracing_count \u001b[38;5;241m==\u001b[39m new_tracing_count)\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow\\python\\eager\\def_function.py:947\u001b[0m, in \u001b[0;36mFunction._call\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m    944\u001b[0m   \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock\u001b[38;5;241m.\u001b[39mrelease()\n\u001b[0;32m    945\u001b[0m   \u001b[38;5;66;03m# In this case we have created variables on the first call, so we run the\u001b[39;00m\n\u001b[0;32m    946\u001b[0m   \u001b[38;5;66;03m# defunned version which is guaranteed to never create variables.\u001b[39;00m\n\u001b[1;32m--> 947\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_stateless_fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)  \u001b[38;5;66;03m# pylint: disable=not-callable\u001b[39;00m\n\u001b[0;32m    948\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_stateful_fn \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    949\u001b[0m   \u001b[38;5;66;03m# Release the lock early so that multiple threads can perform the call\u001b[39;00m\n\u001b[0;32m    950\u001b[0m   \u001b[38;5;66;03m# in parallel.\u001b[39;00m\n\u001b[0;32m    951\u001b[0m   \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock\u001b[38;5;241m.\u001b[39mrelease()\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow\\python\\eager\\function.py:2453\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   2450\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock:\n\u001b[0;32m   2451\u001b[0m   (graph_function,\n\u001b[0;32m   2452\u001b[0m    filtered_flat_args) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_maybe_define_function(args, kwargs)\n\u001b[1;32m-> 2453\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mgraph_function\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_flat\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   2454\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfiltered_flat_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcaptured_inputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgraph_function\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcaptured_inputs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow\\python\\eager\\function.py:1860\u001b[0m, in \u001b[0;36mConcreteFunction._call_flat\u001b[1;34m(self, args, captured_inputs, cancellation_manager)\u001b[0m\n\u001b[0;32m   1856\u001b[0m possible_gradient_type \u001b[38;5;241m=\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPossibleTapeGradientTypes(args)\n\u001b[0;32m   1857\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (possible_gradient_type \u001b[38;5;241m==\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPOSSIBLE_GRADIENT_TYPES_NONE\n\u001b[0;32m   1858\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m executing_eagerly):\n\u001b[0;32m   1859\u001b[0m   \u001b[38;5;66;03m# No tape is watching; skip to running the function.\u001b[39;00m\n\u001b[1;32m-> 1860\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_build_call_outputs(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_inference_function\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   1861\u001b[0m \u001b[43m      \u001b[49m\u001b[43mctx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcancellation_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcancellation_manager\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[0;32m   1862\u001b[0m forward_backward \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_select_forward_and_backward_functions(\n\u001b[0;32m   1863\u001b[0m     args,\n\u001b[0;32m   1864\u001b[0m     possible_gradient_type,\n\u001b[0;32m   1865\u001b[0m     executing_eagerly)\n\u001b[0;32m   1866\u001b[0m forward_function, args_with_tangents \u001b[38;5;241m=\u001b[39m forward_backward\u001b[38;5;241m.\u001b[39mforward()\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow\\python\\eager\\function.py:497\u001b[0m, in \u001b[0;36m_EagerDefinedFunction.call\u001b[1;34m(self, ctx, args, cancellation_manager)\u001b[0m\n\u001b[0;32m    495\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _InterpolateFunctionError(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m    496\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m cancellation_manager \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 497\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m \u001b[43mexecute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    498\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msignature\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    499\u001b[0m \u001b[43m        \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_num_outputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    500\u001b[0m \u001b[43m        \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    501\u001b[0m \u001b[43m        \u001b[49m\u001b[43mattrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    502\u001b[0m \u001b[43m        \u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mctx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    503\u001b[0m   \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    504\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m execute\u001b[38;5;241m.\u001b[39mexecute_with_cancellation(\n\u001b[0;32m    505\u001b[0m         \u001b[38;5;28mstr\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msignature\u001b[38;5;241m.\u001b[39mname),\n\u001b[0;32m    506\u001b[0m         num_outputs\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_outputs,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    509\u001b[0m         ctx\u001b[38;5;241m=\u001b[39mctx,\n\u001b[0;32m    510\u001b[0m         cancellation_manager\u001b[38;5;241m=\u001b[39mcancellation_manager)\n",
      "File \u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow\\python\\eager\\execute.py:54\u001b[0m, in \u001b[0;36mquick_execute\u001b[1;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[0;32m     52\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m     53\u001b[0m   ctx\u001b[38;5;241m.\u001b[39mensure_initialized()\n\u001b[1;32m---> 54\u001b[0m   tensors \u001b[38;5;241m=\u001b[39m \u001b[43mpywrap_tfe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTFE_Py_Execute\u001b[49m\u001b[43m(\u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_handle\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mop_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m     55\u001b[0m \u001b[43m                                      \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     56\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m core\u001b[38;5;241m.\u001b[39m_NotOkStatusException \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m     57\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# The LSTM architecture\n",
    "regressor = Sequential()\n",
    "# First LSTM layer with Dropout regularisation\n",
    "regressor.add(LSTM(units=50, return_sequences=True, input_shape=(X_train.shape[1],1)))\n",
    "regressor.add(Dropout(0.2))\n",
    "# Second LSTM layer\n",
    "regressor.add(LSTM(units=50, return_sequences=True))\n",
    "regressor.add(Dropout(0.2))\n",
    "# Third LSTM layer\n",
    "regressor.add(LSTM(units=50, return_sequences=True))\n",
    "regressor.add(Dropout(0.2))\n",
    "# Fourth LSTM layer\n",
    "regressor.add(LSTM(units=50))\n",
    "regressor.add(Dropout(0.2))\n",
    "# The output layer\n",
    "regressor.add(Dense(units=5))\n",
    "\n",
    "# Compiling the RNN\n",
    "regressor.compile(optimizer='rmsprop',loss='mean_squared_error',metrics='accuracy')\n",
    "# Fitting to the training set\n",
    "regressor.fit(X_train,y_train,epochs=25,batch_size=32)"
   ]
  }
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