Scaling, Normalization, Min Max.
n_informative=5, n_redundant=0, random_state=1) # summarize data before the transform print(X[:3, :]) # define the scaler trans = MinMaxScaler() # transform the data X_norm = trans.fit_transform(X) # summarize data after the transform print(X_norm[:3, :]) Normalization( Z-Score Normalization) Here