roc curve
#ROC curve code snippet from external source(Module notes) def draw_roc( actual, probs ): fpr, tpr, thresholds = metrics.roc_curve( actual, probs, drop_intermediate = False ) auc_score = metrics.roc_auc_score( actual, probs ) plt.figure(figsize=(5, 5)) plt.plot( fpr, tpr, label='ROC curve (area = %0.2f)' % auc_score ) plt.plot([0, 1], [0, 1], 'k--') plt.xlim([0.0, 1.0]) plt.ylim([0.0, 1.05]) plt.xlabel('False Positive Rate or [1 - True Negative Rate]') plt.ylabel('True Positive Rate') plt.title('Receiver operating characteristic example') plt.legend(loc="lower right") plt.show() return None fpr, tpr, thresholds = metrics.roc_curve( y_train_pred_final.Converted, y_train_pred_final.Converted_prob, drop_intermediate = False ) draw_roc(y_train_pred_final.Converted, y_train_pred_final.Converted_prob)