Scaling, Normalization, Min Max.
our wine quality dataset in training and test sets, fit the pipeline to our training set, and predict on our test set. Computing the accuracy yields (point) 956, whereas performing KNN without scaling resulted in an accuracy of (point) 928. Scaling did improve our model performance! from