#false positive rate,fpr= FP/(TN+FP) OR fpr=1-specificty, tpr=sensitivity y_pred_knn_p =knn.predict_proba(X_test)[:,1] models=[y_pred_knn_p] label=['KNN'] # plotting ROC curves plt.figure(figsize=(10, 8)) m=np.arange(1) for m in m: fpr, tpr,thresholds= metrics.roc_curve(y_test,models[m]) print('model:',label[m]) print('thresholds:',np.round(thresholds,3)) print('tpr: ',np.round(tpr,3)) print('fpr: ',np.round(fpr,3)) plt.plot(fpr,tpr,label=label[m]) plt.xlim([0.0,1.0]) plt.ylim([0.0,1.0]) plt.title('ROC curve for Cancer classifer') plt.xlabel('False positive rate (1-specificity)') plt.ylabel('True positive rate (sensitivity)') plt.legend(loc=4,)
MATLAB: Sir, can you please help me to convert this python code into matlab
python matlab
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