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Feature Selection Algorithms-A Survey


Affiliations
1 Dept. of Comp. Sc., Bharathiyar University, Coimbatore, TN, India
2 Dept. of Comp. Sc. & Engg., MAM College of Engineering, Tiruchirappalli, TN, India
     

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Feature Selection plays an important role in data mining. Dealing with excessive number of features has become a computational burden on learning algorithms. Removing irrelevant and redundant features makes data mining task more efficient and improves its accuracy. In this review, different feature selection approaches, relation between them and the various learning algorithms are discussed. Applications that support the use of feature selection technique are also included. We conclude this work by reviewing the contribution of the various feature selection approaches.

Keywords

Feature Selection, Classification, Clustering, Supervised, Unsupervised, Semi-Supervised.
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  • Feature Selection Algorithms-A Survey

Abstract Views: 229  |  PDF Views: 2

Authors

K. Fathima Bibi
Dept. of Comp. Sc., Bharathiyar University, Coimbatore, TN, India
M. Nazreen Banu
Dept. of Comp. Sc. & Engg., MAM College of Engineering, Tiruchirappalli, TN, India

Abstract


Feature Selection plays an important role in data mining. Dealing with excessive number of features has become a computational burden on learning algorithms. Removing irrelevant and redundant features makes data mining task more efficient and improves its accuracy. In this review, different feature selection approaches, relation between them and the various learning algorithms are discussed. Applications that support the use of feature selection technique are also included. We conclude this work by reviewing the contribution of the various feature selection approaches.

Keywords


Feature Selection, Classification, Clustering, Supervised, Unsupervised, Semi-Supervised.