├── .gitignore ├── EDA.ipynb ├── Images ├── FeatureImportance.png ├── Flowchart.png ├── Report-1.jpg ├── Report-2.jpg ├── Report-3.jpg ├── Report-4.jpg ├── Report-5.jpg ├── Report-6.jpg ├── SampleRow.png ├── Table2.png ├── Table3.png └── Table4.png ├── Imbalanced ├── AdaBoost.ipynb ├── Decision Tree.ipynb ├── KNeighborsClassifier.ipynb ├── LDA.ipynb ├── LogisticRegression.ipynb ├── MLPClassifier.ipynb ├── NaiveBayes.ipynb ├── RandomForest.ipynb └── SVC.ipynb ├── Oversampling ├── AdaBoost With Oversampling.ipynb ├── Decision Tree With Oversampling.ipynb ├── KNeighborsClassifier With Oversampling.ipynb ├── LDA with Oversampling.ipynb ├── LogisticRegression with Oversampling.ipynb ├── MLPClassifier With Oversampling.ipynb ├── NaiveBayes With Oversampling.ipynb ├── RandomForest With Oversampling.ipynb └── SVC With Oversampling.ipynb ├── PCA ├── AdaBoost with PCA.ipynb ├── Decision Tree with PCA.ipynb ├── KNeighborsClassifier with PCA.ipynb ├── LogisticRegression with PCA.ipynb ├── MLPClassifier with PCA.ipynb ├── NaiveBayes With PCA.ipynb ├── RandomForest With PCA.ipynb └── SVC with PCA.ipynb ├── README.md ├── Report.pdf ├── Undersampling and Oversampling With PCA ├── Final AdaBoost with PCA.ipynb ├── Final Decision Tree with PCA.ipynb ├── Final KNeighborsClassifier with PCA.ipynb ├── Final MLPClassifier with PCA.ipynb ├── Final NaiveBayes With PCA.ipynb ├── Final RandomForest With PCA.ipynb ├── Final SVC with PCA.ipynb ├── Final_LDA.ipynb └── Final_LogisticRegression.ipynb └── Undersampling ├── AdaBoost With Undersampling.ipynb ├── Decision Tree With Undersampling.ipynb ├── KNeighborsClassifier With Undersampling.ipynb ├── LDA with Undersampling.ipynb ├── LogisticRegression With Undersampling.ipynb ├── MLPClassifier With Undersampling.ipynb ├── NaiveBayes With Undersampling.ipynb ├── RandomForest With Undersampling.ipynb └── SVC With Undersampling.ipynb /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 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