ML: LR, SVM, AdaBoost, RF

Check out the following Python code for turn over prediction using Logistic Regression, Suppor Vector Machine, AdaBoost, Random Forest:

https://github.com/ginger-chuanli-jiang/turnover_Python/blob/main/test_dataframe2.ipynb

Figure1: visualize numerical variable: score1

Figure2: visualize numerical variable: score2

Figure3: intercorrelations among predictor variables

Figure4: feature importances of the forest

Figure5: cross-validation roc curves

Figure6: learning curve: training score and cross-validation score converge to the approximation error; which is the minimum risk achievable by a predictor in the hypothesis class; measure the risk because we restrict ourselves to a specific class.