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Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach

High dimension data are often associated with redundant features and there exist many information-theoretic approaches used to select the most relevant set of features and to reduce the feature size. The three most significant approaches are filter, wrap- per, and embedded approaches. Most filter ap...

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Main Author: Jothi, Neesha
Format: Thesis
Language:English
Published: 2020
Subjects:
QA75.5-76.95 Electronic computers. Computer science
Online Access:http://eprints.usm.my/52445/1/Pages%20from%202.%20Final%20Thesis%20Submission.pdf
http://eprints.usm.my/52445/
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spelling my.usm.eprints.52445 http://eprints.usm.my/52445/ Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach Jothi, Neesha QA75.5-76.95 Electronic computers. Computer science High dimension data are often associated with redundant features and there exist many information-theoretic approaches used to select the most relevant set of features and to reduce the feature size. The three most significant approaches are filter, wrap- per, and embedded approaches. Most filter approaches fail to identify the individual contribution of every feature in each set of features in achieving an optimal feature subset. While the wrapper approaches encounter problems from complex interactions among features and stagnation in local optima. To address, these drawbacks, this study investigates filter and wrapper approaches to develop effective hybrid approaches for feature selection. 2020-11 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/52445/1/Pages%20from%202.%20Final%20Thesis%20Submission.pdf Jothi, Neesha (2020) Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach. PhD thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic QA75.5-76.95 Electronic computers. Computer science
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Jothi, Neesha
Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
description High dimension data are often associated with redundant features and there exist many information-theoretic approaches used to select the most relevant set of features and to reduce the feature size. The three most significant approaches are filter, wrap- per, and embedded approaches. Most filter approaches fail to identify the individual contribution of every feature in each set of features in achieving an optimal feature subset. While the wrapper approaches encounter problems from complex interactions among features and stagnation in local optima. To address, these drawbacks, this study investigates filter and wrapper approaches to develop effective hybrid approaches for feature selection.
format Thesis
author Jothi, Neesha
author_facet Jothi, Neesha
author_sort Jothi, Neesha
title Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
title_short Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
title_full Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
title_fullStr Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
title_full_unstemmed Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
title_sort feature selection method based on hybrid filter-metaheuristic wrapper approach
publishDate 2020
url http://eprints.usm.my/52445/1/Pages%20from%202.%20Final%20Thesis%20Submission.pdf
http://eprints.usm.my/52445/
_version_ 1732946310495993856
score 13.211869

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