What is Feature Scaling? Explain the different feature scaling techniques
Feature scaling is a data preprocessing technique that involves transforming the numerical values of features to a standardized scale.
Feature scaling is a data preprocessing technique that involves transforming the numerical values of features to a standardized scale.
‘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’.
Feature scaling is a data pre-processing technique that transforms the original support of a variable to a different scale.
Partner Ad