Scaling, Normalization, Min Max.
train_test_split(X, y, test_size=0.2, random_state=42) scaler = RobustScaler() scaler.fit(X_train) X_train_scaled = scaler.transform(X_train) X_test_scaled = scaler.transform(X_test) For each feature. Of course, this means it is using less of the data for scaling so it’s more suitable for when