### What is Max Absolute Scaler? Compare it with MinMax Normalization? Why scaling to [-1, 1] might be better than [0, 1] scaling?

‘Max Absolute Scaler’ is another option for preprocessing Training Data.

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‘Max Absolute Scaler’ is another option for preprocessing Training Data.

Another technique that we may wish to use, when preparing our ‘Training Data’, is ‘MinMax Normalization’.

Two basic pre-processing techniques, applicable to Numerical Features, are ‘Centering’ and ‘Scaling’.

Feature scaling is a data pre-processing technique that transforms the original support of a variable to a different scale.

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