Feature Selection Based on Support Vector Machine
Abstract：This paper is devoted to study a leature election method based on support vector machine feature weight. Experiments with two kinds of data taken from UCI machine learning repository show that feature weight method is superior to F-score method and SVM on the classification results.
Keywords：Feature selectlon~ feature weight methodY-score methodsupport vector machinesmisclassification rate
Publication Date：2011-01-01
Online Publishing Date：2026-08-28(First online date of this platform, not the publication date of the document)
Pages：5( 23-27 )