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Performed feature engineering, cross-validation (5 fold) on baseline and cost-sensitive (accounting for class imbalance) Decision trees and Logistic Regression models and compared performance. Used appropriate performance metrics i.e., AUC ROC, Average Precision and Balanced Accuracy. Outperformed baseline model.

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auc-roc-score average-precision balanced-accuracy-scores class-imbalance-problem cross-validation decision-trees feature-engineering logistic-regression performance-metrics

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