Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset
Incorporating knowledge from domain expert to a classifier is one of the techniques which require to be considered in solving imbalanced dataset problems. In this study, the proposed technique is a development to extend the process for imbalanced dataset where the individual classification system ha...
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my.utm.295932017-02-04T07:00:23Z http://eprints.utm.my/id/eprint/29593/ Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset Adam, A. Shapiai, Mohd. Ibrahim Ibrahim, Zuwairie Khalid, Marzuki TK Electrical engineering. Electronics Nuclear engineering Incorporating knowledge from domain expert to a classifier is one of the techniques which require to be considered in solving imbalanced dataset problems. In this study, the proposed technique is a development to extend the process for imbalanced dataset where the individual classification system has already been designed for balanced data set. This paper introduces a methodology and preliminary results which are used to investigate whether the proposed approach is possible to improve a classifier's performance when domain expert is employed to the nai¨ve bayes classifier. Domain expert is an additional knowledge which is produced by expert system (neural network) and then become an additional input to the nai¨ve bayes classifier. By using several benchmark data sets from the UCI Machine Learning Repository, the results of the proposed technique show an improvement as compared to the conventional nai¨ve bayes classifier. IEEE 2011 Book Section PeerReviewed Adam, A. and Shapiai, Mohd. Ibrahim and Ibrahim, Zuwairie and Khalid, Marzuki (2011) Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset. In: 2011 4th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO). IEEE, Danvers, Massachusetts, 1-5 . ISBN 978-1-4577-0003-3 http://dx.doi.org/10.1109/ICMSAO.2011.5775584 10.1109/ICMSAO.2011.5775584 |
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TK Electrical engineering. Electronics Nuclear engineering Adam, A. Shapiai, Mohd. Ibrahim Ibrahim, Zuwairie Khalid, Marzuki Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset |
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Incorporating knowledge from domain expert to a classifier is one of the techniques which require to be considered in solving imbalanced dataset problems. In this study, the proposed technique is a development to extend the process for imbalanced dataset where the individual classification system has already been designed for balanced data set. This paper introduces a methodology and preliminary results which are used to investigate whether the proposed approach is possible to improve a classifier's performance when domain expert is employed to the nai¨ve bayes classifier. Domain expert is an additional knowledge which is produced by expert system (neural network) and then become an additional input to the nai¨ve bayes classifier. By using several benchmark data sets from the UCI Machine Learning Repository, the results of the proposed technique show an improvement as compared to the conventional nai¨ve bayes classifier. |
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Book Section |
author |
Adam, A. Shapiai, Mohd. Ibrahim Ibrahim, Zuwairie Khalid, Marzuki |
author_facet |
Adam, A. Shapiai, Mohd. Ibrahim Ibrahim, Zuwairie Khalid, Marzuki |
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Adam, A. |
title |
Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset |
title_short |
Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset |
title_full |
Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset |
title_fullStr |
Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset |
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Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset |
title_sort |
artificial neural network — naïve bayes fusion for solving classification problem of imbalanced dataset |
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IEEE |
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2011 |
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http://eprints.utm.my/id/eprint/29593/ http://dx.doi.org/10.1109/ICMSAO.2011.5775584 |
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