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A Study on Meta Heuristic Algorithms for Feature Selection

  • Rajalakshmi Shenbaga Moorthy
  • P. Pabitha
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)

Abstract

Vast number of feature selection methods are available to evaluate the best subset of features as the data in the real world is growing bigger and bigger. Feature selection methods are essential in order to reduce the processing time of the model, improving the accuracy of the model, and to avoid the problem of curse of dimensionality. The objective of this paper is to elaborate feature selection which is essential for classification and prediction tasks. We concentrate on meta heuristic algorithms for optimal feature subset selection. We also made a comparison of the characteristics of meta heuristic algorithms.

Keywords

Feature selection Meta heuristic algorithm 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSt. Joseph’s Institute of TechnologyChennaiIndia
  2. 2.Department of Computer TechnologyMadras Institute of Technology, Anna UniversityChennaiIndia

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