Pcos Detection

Pcos Detection/Model/README.md

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+# PCOS Detection
+
+## 🎯 GOAL
+
+The aim of the project is to build a model which would predict whether a person has PCOS (Polycystic Ovary Syndrome).
+
+## 🧵 DATASET
+
+The dataset was taken from Kaggle.
+
+## 🧾 DESCRIPTION
+
+In this project, we compare the accuracies of different models to predict PCOS in a person.
+
+## 🧮 WHAT I HAD DONE
+
+Steps followed:
+- Downloaded the dataset from Kaggle.
+- Checked for null values and performed exploratory data analysis.
+- Built models using various algorithms.
+- Compared the accuracies.
+- Performed cross-validation on all the algorithms to see if the accuracies improve.
+
+## 🚀 Models Implemented
+
+1. Logistic Regression
+2. Decision Tree
+3. Random Forest
+4. Gradient Boosting
+5. Adaboost
+6. Naive Bayes
+7. Support Vector Machine
+8. K-Nearest Neighbors
+
+## 📚 LIBRARIES NEEDED
+
+- Pandas
+- Matplotlib
+- Seaborn
+- Numpy
+- Sklearn
+
+## 📊 Exploratory Data Analysis Results
+
+![Confusion Matrix](https://raw.githubusercontent.com/abhisheks008/ML-Crate/1292b54868a3ea93e7520149b56450057ff92197/Pcos%20Detection/Images/Screenshot%202024-06-07%20114101.png)
+
+
+![Class Distribution With SMOTE](https://raw.githubusercontent.com/abhisheks008/ML-Crate/1292b54868a3ea93e7520149b56450057ff92197/Pcos%20Detection/Images/Screenshot%202024-06-07%20114118.png)
+
+
+## 📈 Performance of the Models based on the Accuracy Scores
+
+| Classifier              | Accuracy   |
+|-------------------------|------------|
+| Logistic Regression     | 0.703704   |
+| Decision Tree           | 0.629630   |
+| Random Forest           | 0.685185   |
+| Gradient Boosting       | 0.731481   |
+| AdaBoost                | 0.685185   |
+| Naive Bayes             | 0.518519   |
+| Support Vector Machine  | 0.305556   |
+| K-Nearest Neighbors     | 0.694444   |
+
+## 📢 CONCLUSION
+
+From this project, we conclude that Gradient Boosting has the highest accuracy among all the algorithms, followed by Logistic Regression, Random Forest, AdaBoost, and KNN.
+
+## ✒️ Contribution by
+
+Payal Sinha  
+GitHub: [payalsinha12](https://github.com/payalsinha12)

Pcos Detection/requirements.txt

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+pandas==1.3.4
+numpy==1.21.4
+pandas==1.3.5
+matplotlib==3.5.1
+scikit-learn==1.0.1
+seaborn==0.11.2