Abstract
The feature reduction is one of the core techniques in text categorization. But there is no consideration of text position factor to the differentiation of labeling text capability in the method of weighting basing on multi-information (MI) in features. So in this paper, we put forward an improved feature selection method that based on MI. By adding the amending parameters in different positions, we have increased the using efficiency about the character information. The result of experiment shows that this method has improved the accuracy of the text classification.
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© 2009 Springer-Verlag Berlin Heidelberg
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Liu, H., Su, Z., Yao, Z., Liu, S. (2009). An Improved Feature Selection for Categorization Based on Mutual Information. In: Liu, W., Luo, X., Wang, F.L., Lei, J. (eds) Web Information Systems and Mining. WISM 2009. Lecture Notes in Computer Science, vol 5854. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05250-7_9
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DOI: https://doi.org/10.1007/978-3-642-05250-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05249-1
Online ISBN: 978-3-642-05250-7
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