The effect of term weighting measures on feature selection
Feature selection is an important stage in any text mining classification techniques. In this dissertation, we study and analyze Categorical Term Descriptor (CTD) (Bong, C.H., 2001) feature selection method. which gives comparative accuracy results compared to other well-known feature selection meth...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/1714/2/Latifah%20Loh%20Abdullah.pdf |
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| Summary: | Feature selection is an important stage in any text mining classification techniques. In this dissertation, we study and analyze Categorical Term Descriptor (CTD) (Bong, C.H., 2001) feature selection method. which gives comparative accuracy results compared to other well-known feature selection method like Information Gain and Chi-Square. Our goal is to evaluate the significance of each term weighting measure that forms the CTD method. Our experimental results have shown taht CTD does not handle datasets that contain misclassifications. We have proven that CTD performs well in categories which are distinct as opposed to general and miscellaneous categories. |
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