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.
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.