White Papers
Modified Logistic Regression: An Approximation to SVM and Its Applications in Large-Scale Text Categorization
Overview Logistic Regression (LR) has been widely used in statistics for many years, and has received extensive study in machine learning community recently due to its close relations to Support Vector Machines (SVM) and Ad-a-Boost. This paper uses a modified version of LR to approximate the optimization of SVM by a sequence of unconstrained optimization problems. The paper proves that the approximation will converge to SVM, and propose an iterative algorithm called "MLR-CG" which uses Conjugate Gradient as its inner loop. Multiclass version "MMLR-CG" is also obtained after simple modifications.
- Publisher
- Carnegie Mellon University
- File Format
- Date Published
- Mar 20, 2008
- Format
- White Papers
- Topics
- Learning Management Systems, Software Engineering
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