Feature selection, L1 vs. L2 regularization, and rotational invariance Andrew Y. Ng Computer Science Department, Stanford University, Stanford, CA 94305, USA Abstract - Andrew Ng - Document - PDFSEARCH.IO - Document Search Engine

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	Feature selection, L1 vs. L2 regularization, and rotational invariance Andrew Y. Ng Computer Science Department, Stanford University, Stanford, CA 94305, USA Abstract Add to Reading List Document Date: 2008-12-01 11:20:54 Open Document File Size: 170,05 KB Share Result on Facebook City Banff / / Company Computer Research Laboratory / Cambridge University Press / International Thomas Publishing / John Wiley & Sons / / Country Jordan / Canada / / / Facility Stanford University / / IndustryTerm good feature selection algorithm / perceptron algorithm / additive linear online prediction algorithm / perceptron learning algorithm / linear-threshold algorithm / invariant algorithm / invariant algorithms / generative learning algorithm / selection algorithms / then computing x0 / stochastic learning algorithm / invariant learning algorithm / feature selection algorithms / learning algorithm / / Organization Univ. of California Santa Cruz / Cambridge University / Stanford University / Andrew Y. Ng Computer Science Department / Department of the Interior / Princeton Univ. / / Person Chris Manning / Rajat Raina / Andrew Y. Ng / Kristina Toutanova / Pieter Abbeel / Yoram Singer / Morgan Kaufmann / / Position author / vP / Prime Minister / / Product L1 / / ProgrammingLanguage L / C / / ProvinceOrState California / / PublishedMedium IEEE Transactions on Information Theory / Machine Learning / Journal of Machine Learning Research / / SportsLeague Stanford University / / Technology rotationally invariant learning algorithm / learning algorithm / Any algorithm / generative learning algorithm / Neural network / linear-threshold algorithm / additive linear online prediction algorithm / good feature selection algorithm / Lasso algorithm / appealing algorithm / non-rotationally invariant algorithms / selection algorithms / Machine Learning / rotationally invariant algorithms / feature selection algorithms / rotationally invariant algorithm / stochastic learning algorithm / The perceptron algorithm / perceptron learning algorithm / / SocialTag Econometrics M-estimators Regression analysis Maximum likelihood Supervised learning Rotation matrix Regularization Linear regression Dimensional analysis Statistics