Abstract
In order to improve the classification accuracy and speed, classification of the structure of this paper has been improved, is proposes a combination of Bayesian and k-nearest neighbor classifier model, which combines Bayesian classification method of classification rate fast and k-nearest neighbor method with higher classification accuracy advantages. Experimental results show that the method to ensure the classification rate under the premise of effectively improving the classification accuracy.
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Tao, W., Liang, H., Liu, Y. (2013). The Improved Text Classification Method Based on Bayesian and k-NN. In: Du, Z. (eds) Proceedings of the 2012 International Conference of Modern Computer Science and Applications. Advances in Intelligent Systems and Computing, vol 191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33030-8_10
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DOI: https://doi.org/10.1007/978-3-642-33030-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33029-2
Online ISBN: 978-3-642-33030-8
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