A hybrid filter/wrapper approach of feature selection using information theory

Marc Sebban; Richard Nock

doi:10.1016/s0031-3203(01)00084-x

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A hybrid filter/wrapper approach of feature selection using information theory

Marc Sebban Richard Nock

Year: 2002 Journal: Pattern Recognition Vol: 35 (4)Pages: 835-846 Publisher: Elsevier BV

DOI: 10.1016/s0031-3203(01)00084-x

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Keywords:

Feature selection Filter (signal processing) Computer science k-nearest neighbors algorithm Artificial intelligence Pattern recognition (psychology) Feature (linguistics) Minimum redundancy feature selection Focus (optics) Data mining Exploit Selection (genetic algorithm) Graph theory Algorithm Mathematics

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Topics

Rough Sets and Fuzzy Logic

Physical Sciences → Computer Science → Computational Theory and Mathematics

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

A hybrid filter/wrapper approach of feature selection using information theory

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