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Literature Review on Feature Selection Methods for High-Dimensional Data

by D. Asir Antony Gnana Singh, S. Appavu Alias Balamurugan, E. Jebamalar Leavline
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 1
Year of Publication: 2016
Authors: D. Asir Antony Gnana Singh, S. Appavu Alias Balamurugan, E. Jebamalar Leavline
10.5120/ijca2016908317

D. Asir Antony Gnana Singh, S. Appavu Alias Balamurugan, E. Jebamalar Leavline . Literature Review on Feature Selection Methods for High-Dimensional Data. International Journal of Computer Applications. 136, 1 ( February 2016), 9-17. DOI=10.5120/ijca2016908317

@article{ 10.5120/ijca2016908317,
author = { D. Asir Antony Gnana Singh, S. Appavu Alias Balamurugan, E. Jebamalar Leavline },
title = { Literature Review on Feature Selection Methods for High-Dimensional Data },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 1 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 9-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number1/24116-2016908317/ },
doi = { 10.5120/ijca2016908317 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:37:03.934064+05:30
%A D. Asir Antony Gnana Singh
%A S. Appavu Alias Balamurugan
%A E. Jebamalar Leavline
%T Literature Review on Feature Selection Methods for High-Dimensional Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 1
%P 9-17
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Feature selection plays a significant role in improving the performance of the machine learning algorithms in terms of reducing the time to build the learning model and increasing the accuracy in the learning process. Therefore, the researchers pay more attention on the feature selection to enhance the performance of the machine learning algorithms. Identifying the suitable feature selection method is very essential for a given machine learning task with high-dimensional data. Hence, it is required to conduct the study on the various feature selection methods for the research community especially dedicated to develop the suitable feature selection method for enhancing the performance of the machine learning tasks on high-dimensional data. In order to fulfill this objective, this paper devotes the complete literature review on the various feature selection methods for high-dimensional data.

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Index Terms

Computer Science
Information Sciences

Keywords

Introduction to variable and feature selection information gain-based feature selection gain ratio-based feature selection symmetric uncertainty-based feature selection subset-based feature selection ranking-based feature selection wrapper-based feature selection embedded-based feature selection filter-based feature selection hybrid feature selection selecting feature from high-dimensional data.

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