Scaling, Normalization, Min Max.
chosen by our gridsearch, along with the accuracy and classification report of the predictions on the hold-out set. In [21]: print(cv.best_params_) {'knn__n_neighbors': 41} In [22]: print(cv.score(X_test, y_test)) 0.956 In [23]: print(classification_report(y_test, y_pred)) precision recall f1-score