Start Submission Become a Reviewer

Reading: A Meta-Heuristic Regression-Based Feature Selection for Predictive Analytics

Download

A- A+
dyslexia friendly

Research Papers

A Meta-Heuristic Regression-Based Feature Selection for Predictive Analytics

Authors:

Bharat Singh ,

Department of Information Technology, Indian Institute of Information Technology, Allahabad, India, IN
X close

O P Vyas

Department of Information Technology, Indian Institute of Information Technology, Allahabad, India, IN
X close

Abstract

A high-dimensional feature selection having a very large number of features with an optimal feature subset is an NP-complete problem. Because conventional optimization techniques are unable to tackle large-scale feature selection problems, meta-heuristic algorithms are widely used. In this paper, we propose a particle swarm optimization technique while utilizing regression techniques for feature selection. We then use the selected features to classify the data. Classification accuracy is used as a criterion to evaluate classifier performance, and classification is accomplished through the use of k-nearest neighbour (KNN) and Bayesian techniques. Various high dimensional data sets are used to evaluate the usefulness of the proposed approach. Results show that our approach gives better results when compared with other conventional feature selection algorithms.
DOI: http://doi.org/10.2481/dsj.14-032
How to Cite: Singh, B. & Vyas, O.P., (2014). A Meta-Heuristic Regression-Based Feature Selection for Predictive Analytics. Data Science Journal. 13, pp.106–118. DOI: http://doi.org/10.2481/dsj.14-032
84
Views
80
Downloads
Published on 06 Nov 2014.
Peer Reviewed

Downloads

  • PDF (EN)

    comments powered by Disqus