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Feature Selection Algorithms – A Survey

K. Fathima Bibi, Dr. M. Nazreen Banu


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.


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

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