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Feature Selection with Mutual Information for Regression Problems

Selecting relevant features for machine learning modeling improves the performance of the learning methods. Mutual information (MI) is known to be used as relevant criterion for selecting feature subsets from input dataset with a nonlinear relationship to the predicting attribute. However, mutu...

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Main Authors: Muhammad Aliyu, Sulaiman, Jane, Labadin
Format: Conference or Workshop Item
Language:English
Published: 2015
Subjects:
T Technology (General)
Online Access:http://ir.unimas.my/id/eprint/13447/1/Feature%20Selection%20with%20Mutual%20Information%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/13447/
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spelling my.unimas.ir.134472017-02-14T05:47:20Z http://ir.unimas.my/id/eprint/13447/ Feature Selection with Mutual Information for Regression Problems Muhammad Aliyu, Sulaiman Jane, Labadin T Technology (General) Selecting relevant features for machine learning modeling improves the performance of the learning methods. Mutual information (MI) is known to be used as relevant criterion for selecting feature subsets from input dataset with a nonlinear relationship to the predicting attribute. However, mutual information estimator suffers the following limitation; it depends on smoothing parameters, the feature selection greedy methods lack theoretically justified stopping criteria and in theory it can be used for both classification and regression problems, however in practice more often it formulation is limited to classification problems. This paper investigates a proposed improvement on the three limitations of the Mutual Information estimator (as mentioned above), through the use of resampling techniques and formulation of mutual information based on differential entropic for regression problems. 2015 Conference or Workshop Item PeerReviewed text en http://ir.unimas.my/id/eprint/13447/1/Feature%20Selection%20with%20Mutual%20Information%20%28abstract%29.pdf Muhammad Aliyu, Sulaiman and Jane, Labadin (2015) Feature Selection with Mutual Information for Regression Problems. In: 2015 9th International Conference on IT in Asia (CITA) : Transforming Big Data into Knowledge, 4-5 August 2015, Kuching, Sarawak Malaysia.
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Muhammad Aliyu, Sulaiman
Jane, Labadin
Feature Selection with Mutual Information for Regression Problems
description Selecting relevant features for machine learning modeling improves the performance of the learning methods. Mutual information (MI) is known to be used as relevant criterion for selecting feature subsets from input dataset with a nonlinear relationship to the predicting attribute. However, mutual information estimator suffers the following limitation; it depends on smoothing parameters, the feature selection greedy methods lack theoretically justified stopping criteria and in theory it can be used for both classification and regression problems, however in practice more often it formulation is limited to classification problems. This paper investigates a proposed improvement on the three limitations of the Mutual Information estimator (as mentioned above), through the use of resampling techniques and formulation of mutual information based on differential entropic for regression problems.
format Conference or Workshop Item
author Muhammad Aliyu, Sulaiman
Jane, Labadin
author_facet Muhammad Aliyu, Sulaiman
Jane, Labadin
author_sort Muhammad Aliyu, Sulaiman
title Feature Selection with Mutual Information for Regression Problems
title_short Feature Selection with Mutual Information for Regression Problems
title_full Feature Selection with Mutual Information for Regression Problems
title_fullStr Feature Selection with Mutual Information for Regression Problems
title_full_unstemmed Feature Selection with Mutual Information for Regression Problems
title_sort feature selection with mutual information for regression problems
publishDate 2015
url http://ir.unimas.my/id/eprint/13447/1/Feature%20Selection%20with%20Mutual%20Information%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/13447/
_version_ 1644511662944813056
score 13.211869

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