Building an Ensemble of Fine-Tuned Naive Bayesian Classifiers for Text Classification

Text classification is one domain in which the naive Bayesian (NB) learning algorithm performs remarkably well. However, making further improvement in performance using ensemble-building techniques proved to be a challenge because NB is a stable algorithm. This work shows that, while an ensemble of...

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Bibliographic Details

Published in:	Entropy (Basel, Switzerland) Vol. 20; no. 11; p. 857
Main Authors:	El Hindi, Khalil, AlSalman, Hussien, Qasem, Safwan, Al Ahmadi, Saad
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 07.11.2018 MDPI
Subjects:	Accuracy Algorithms Bayesian analysis Classification Classifiers Datasets ensembles of classifiers fine-tuning naive Bayesian algorithm Machine learning naive Bayesian learning Neural networks Probability distribution Text categorization text classification
ISSN:	1099-4300, 1099-4300
Online Access:	Get full text
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