Is it best to apply MinMaxScaler to your dataset before splitting into training and Validation set or after splitting
You want to scale before training on the training set. After that, you scale the test and validation using the same mean and variance (i.e. train mean and variance) before inference.
I'm really confused as to when I should apply MinMaxScaler or scaling in general to my dataset, whether is before splitting into train_test_split or after splitting into training and validation split, then fit and transform on X_train and transform on X_test. Really confused about what the general rule of thumb is in applying this...