Friday, August 26, 2011

L1 regularisation Is efficient for selecting relevant features

Andrew Ng has proven in his ICML-2004 paper that sample complexity grows linearly in the number of irrelevant features when using L2 regularisation (in logistic regression, support vector machine, and back-propagation neural network), but only logarithmically when using L1 regularisation (in logistic regression).

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