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- function [X_norm, mu, sigma] = featureNormalize(X)
- %FEATURENORMALIZE Normalizes the features in X
- % FEATURENORMALIZE(X) returns a normalized version of X where
- % the mean value of each feature is 0 and the standard deviation
- % is 1. This is often a good preprocessing step to do when
- % working with learning algorithms.
- mu = mean(X);
- X_norm = bsxfun(@minus, X, mu);
- sigma = std(X_norm);
- X_norm = bsxfun(@rdivide, X_norm, sigma);
- % ============================================================
- end
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