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Bayesian Multinomial Naïve Bayes Classifier to Text Classification

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Advanced Multimedia and Ubiquitous Engineering (FutureTech 2017, MUE 2017)

Abstract

Text classification is the task of assigning predefined classes to free-text documents, and it can provide conceptual views of document collections. The multinomial naïve Bayes (NB) classifier is one NB classifier variant, and it is often used as a baseline in text classification. However, multinomial NB classifier is not fully Bayesian. This study proposes a Bayesian version NB classifier. Finally, experimental results on 20 newsgroup show that Bayesian multinomial NB classifier with suitable Dirichlet hyper-parameters has similar performance with multinomial NB classifier.

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Notes

  1. 1.

    20 newsgroup data can be available online from http://mlcomp.org/datasets/379.

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Acknowledgments

We thank the financial support from National Science Foundation of China (ID: 71403255), and Key Technologies R&D Program of Chinese 12th Five-Year Plan (2011–2015) (ID: 2015BAH25F01). Our gratitude also goes to the anonymous reviewers for their valuable comments.

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Correspondence to Zheng Wang .

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Xu, S., Li, Y., Wang, Z. (2017). Bayesian Multinomial Naïve Bayes Classifier to Text Classification. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_57

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  • DOI: https://doi.org/10.1007/978-981-10-5041-1_57

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