Classification, Support Vector Machine, Roc Curve, Rbf Kernels.
metrics.roc_auc_score(y_test, y_te_prob1) y_te_prob2 = lsvcr_model.predict_proba(X_te_scaled)[::,1] fpr2, tpr2, _ = metrics.roc_curve(y_test, y_te_prob2, pos_label = 'poor') auc2 = metrics.roc_auc_score(y_test, y_te_prob2) plt.figure(figsize=(8,6)) plt.plot(fpr1,tpr1,label="Poly,