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feature normalization

Replacing each raw feature value $x$ with $z=(x-\mu)/\sigma$ , computed once from the training set, so every feature ends with mean $0$ and variance $1$ .

Examples

For the dataset $4,8,12,16$ : mean $10$ , standard deviation about $4.47$ , so $x=16$ standardizes to about $1.34$ .