Cut Off, Lift, Binary Classification, Model Performance, Performance Metrics.
random import matplotlib.pyplot as plt from sklearn.metrics import roc_auc_score, roc_curve Then we create the data that we need. We need unique ID’s, target values and score values that model predict. CUSTOMERID: unique id for a customer CHURN_TARGET: a customer is churn(1) or not (0) MODEL_SCORE: