Abstract
An improved naïve Bayes classifier is proposed. The method includes aspects of improvement: to get a reduced text feature word set by filtering the synonym, to iterate two different feature selection methods, and to effectively improve the representative feature set. The experimental results show that this method can effectively improve the performance of naïve Bayes classifier.
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Acknowledgments
This work was supported by the Science and Technology Program of Beijing Municipal Commission of Education (no. KM201410028020 and no. KM201310028020) and the 2014 Youth Talent Development Plan of Beijing City-Owned University (no. CIT&TCD201404155).
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Lin, Y., Wang, J., Zou, R. (2015). An Improved Naïve Bayes Classifier Method in Public Opinion Analysis. In: Wong, W. (eds) Proceedings of the 4th International Conference on Computer Engineering and Networks. Lecture Notes in Electrical Engineering, vol 355. Springer, Cham. https://doi.org/10.1007/978-3-319-11104-9_26
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DOI: https://doi.org/10.1007/978-3-319-11104-9_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11103-2
Online ISBN: 978-3-319-11104-9
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