A Novel Feature Selection and Extraction Technique for Classification

Kratarth Goel; Raunaq Vohra; Ainesh Bakshi

doi:10.1109/SMC.2014.6974562

paper

A Novel Feature Selection and Extraction Technique for Classification

arXiv:1412.7934 · doi:10.1109/SMC.2014.6974562

Abstract

This paper presents a versatile technique for the purpose of feature selection and extraction - Class Dependent Features (CDFs). We use CDFs to improve the accuracy of classification and at the same time control computational expense by tackling the curse of dimensionality. In order to demonstrate the generality of this technique, it is applied to handwritten digit recognition and text categorization.

2 pages, 2 tables, published at IEEE SMC 2014