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Article:A Study on the Analysis of Genetic Algorithms with Various Classification Techniques for Feature Selection

by Mrs.E.P.Ephzibah, Mrs. B. Sarojini, Mrs. J.Emerald Sheela
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 8 - Number 8
Year of Publication: 2010
Authors: Mrs.E.P.Ephzibah, Mrs. B. Sarojini, Mrs. J.Emerald Sheela
10.5120/1226-1784

Mrs.E.P.Ephzibah, Mrs. B. Sarojini, Mrs. J.Emerald Sheela . Article:A Study on the Analysis of Genetic Algorithms with Various Classification Techniques for Feature Selection. International Journal of Computer Applications. 8, 8 ( October 2010), 33-37. DOI=10.5120/1226-1784

@article{ 10.5120/1226-1784,
author = { Mrs.E.P.Ephzibah, Mrs. B. Sarojini, Mrs. J.Emerald Sheela },
title = { Article:A Study on the Analysis of Genetic Algorithms with Various Classification Techniques for Feature Selection },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 8 },
number = { 8 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume8/number8/1226-1784/ },
doi = { 10.5120/1226-1784 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:56:55.686651+05:30
%A Mrs.E.P.Ephzibah
%A Mrs. B. Sarojini
%A Mrs. J.Emerald Sheela
%T Article:A Study on the Analysis of Genetic Algorithms with Various Classification Techniques for Feature Selection
%J International Journal of Computer Applications
%@ 0975-8887
%V 8
%N 8
%P 33-37
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the world of curse of dimensionality feature selection plays a very important role in reducing the entire feature collection with the limited subset of features. Reducing the number of features pave way for various advantaged as well as simplifies the task. Feature selection means finding the suitable set of features which will contribute the most of it to the solution with minimal or null error rate. Selected features are to be tested with the help of classifiers, so that the subset of selected features can be proved to be optimal when compared to other features subsets individually as well as a group. Genetic algorithms are now days play a vital role among any other methodology in selecting the features based on the Theory of Evolution and on the “Survival of the fitness”. It is a heuristic approach. To cooperate with the GA approach we have the classifiers which will go hand in hand to bring out the final set of features along with their prediction accuracy. In this paper I have analyzed four of the classifiers and compared them with their performance and the unit of accuracy.

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Index Terms

Computer Science
Information Sciences

Keywords

Feature Selection Genetic Algorithm SVM KNN Fuzzy Rough Set Neural Networks classification

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