Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique

Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique

In this paper, the one-way ANOVA model and its application in Bayesian multi-class variable selection is considered. A full Bayesian bootstrap prior ANOVA test function is developed within the framework of parametric empirical Bayes. The test function developed was later used for variable screening...

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Main Authors: Oyebayo Ridwan Olaniran, Mohd Asrul Affendi Abdullah
Format: Article
Language:English
Published: Austrian Statistical Society 2019-01-01
Series:Austrian Journal of Statistics
Online Access:http://www.ajs.or.at/index.php/ajs/article/view/806
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spelling doaj-433ca723768f4afabc54d9dde449bd432021-04-22T12:32:08ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2019-01-0148210.17713/ajs.v48i2.806Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior TechniqueOyebayo Ridwan Olaniran0Mohd Asrul Affendi Abdullah1Universiti Tun Hussein Onn MalaysiaDepartment of Mathematics and Statistics, Faculty of Applied Science and Technology, Universiti Tun Hussein Onn Malaysia, Pagoh, Educational Hub, 84600 Pagoh, Johor, Malaysia In this paper, the one-way ANOVA model and its application in Bayesian multi-class variable selection is considered. A full Bayesian bootstrap prior ANOVA test function is developed within the framework of parametric empirical Bayes. The test function developed was later used for variable screening in multiclass classification scenario. Performance comparison between the proposed method and existing classical ANOVA method was achieved using simulated and real life gene expression datasets. Analysis results revealed lower false positive rate and higher sensitivity for the proposed method. http://www.ajs.or.at/index.php/ajs/article/view/806
collection DOAJ
language English
format Article
sources DOAJ
author Oyebayo Ridwan Olaniran
Mohd Asrul Affendi Abdullah
spellingShingle Oyebayo Ridwan Olaniran
Mohd Asrul Affendi Abdullah
Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique
Austrian Journal of Statistics
author_facet Oyebayo Ridwan Olaniran
Mohd Asrul Affendi Abdullah
author_sort Oyebayo Ridwan Olaniran
title Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique
title_short Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique
title_full Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique
title_fullStr Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique
title_full_unstemmed Bayesian Variable Selection for Multiclass Classification using Bootstrap Prior Technique
title_sort bayesian variable selection for multiclass classification using bootstrap prior technique
publisher Austrian Statistical Society
series Austrian Journal of Statistics
issn 1026-597X
publishDate 2019-01-01
description In this paper, the one-way ANOVA model and its application in Bayesian multi-class variable selection is considered. A full Bayesian bootstrap prior ANOVA test function is developed within the framework of parametric empirical Bayes. The test function developed was later used for variable screening in multiclass classification scenario. Performance comparison between the proposed method and existing classical ANOVA method was achieved using simulated and real life gene expression datasets. Analysis results revealed lower false positive rate and higher sensitivity for the proposed method.
url http://www.ajs.or.at/index.php/ajs/article/view/806
work_keys_str_mv AT oyebayoridwanolaniran bayesianvariableselectionformulticlassclassificationusingbootstrappriortechnique
AT mohdasrulaffendiabdullah bayesianvariableselectionformulticlassclassificationusingbootstrappriortechnique
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