New Feature Subset Selection Algorithm Using Class Association Rules Mining-Reference-Cited by-同舟云学术

New Feature Subset Selection Algorithm Using Class Association Rules Mining

Published:2011-04 Issue: Volume:474-476 Page:622-625
ISSN:1662-9795
Container-title:Key Engineering Materials
language:
Short-container-title:KEM

Author:

Zhang Shou Juan¹,Zhou Quan¹

Affiliation:

1. China Academy of Space Technology

Abstract

A new feature subset selection algorithm using class association rules mining is proposed in this paper. Firstly, the algorithm mines rules with features as antecedences and class attributes as consequences. Then, it selects the strongest rules one by one, and all the rules’ antecedences make up of the selected feature subset. Experimental results on 10 real data sets show that the proposed algorithm produces a remarkable advantage in enormously reducing the number of the features while keeping quite high classification accuracy compared with other existing seven algorithms. This algorithm can offer an available preprocess technique for pattern recognition, machine learning and data mining.

Publisher

Trans Tech Publications, Ltd.

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://www.scientific.net/KEM.474-476.622.pdf

Reference11 articles.

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