Bregman Distance to L1 Regularized Logistic Regression

Details Bregman Distance to L1 Regularized Logistic Regression Bregman Distance to L1 Regularized Logistic Regression

2010-04-21

arxiv.org/abs/1004.3814v1

Computer Science

Learning

8 pages, 3 images, shorter version published in ICPR 2008 by same authors.

Scientific paper

In this work we investigate the relationship between Bregman distances and regularized Logistic Regression model. We present a detailed study of Bregman Distance minimization, a family of generalized entropy measures associated with convex functions. We convert the L1-regularized logistic regression into this more general framework and propose a primal-dual method based algorithm for learning the parameters. We pose L1-regularized logistic regression into Bregman distance minimization and then apply non-linear constrained optimization techniques to estimate the parameters of the logistic model.

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