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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| Format: | Thesis |
| Language: | English |
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Faculty of Computer Science and Information Technology
2007
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| Online Access: | http://ir.unimas.my/id/eprint/1714/ http://ir.unimas.my/id/eprint/1714/2/Latifah%20Loh%20Abdullah.pdf |
| _version_ | 1848834818304901120 |
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| author | Latifah Loh, Abdullah |
| author_facet | Latifah Loh, Abdullah |
| author_sort | Latifah Loh, Abdullah |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T05:58:01Z |
| format | Thesis |
| id | unimas-1714 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T05:58:01Z |
| publishDate | 2007 |
| publisher | Faculty of Computer Science and Information Technology |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-17142023-03-07T08:09:58Z http://ir.unimas.my/id/eprint/1714/ The effect of term weighting measures on feature selection Latifah Loh, Abdullah T Technology (General) 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. Faculty of Computer Science and Information Technology 2007 Thesis NonPeerReviewed text en http://ir.unimas.my/id/eprint/1714/2/Latifah%20Loh%20Abdullah.pdf Latifah Loh, Abdullah (2007) The effect of term weighting measures on feature selection. Masters thesis, Universiti Malaysia Sarawak (UNIMAS). |
| spellingShingle | T Technology (General) Latifah Loh, Abdullah The effect of term weighting measures on feature selection |
| title | The effect of term weighting measures on feature selection |
| title_full | The effect of term weighting measures on feature selection |
| title_fullStr | The effect of term weighting measures on feature selection |
| title_full_unstemmed | The effect of term weighting measures on feature selection |
| title_short | The effect of term weighting measures on feature selection |
| title_sort | effect of term weighting measures on feature selection |
| topic | T Technology (General) |
| url | http://ir.unimas.my/id/eprint/1714/ http://ir.unimas.my/id/eprint/1714/2/Latifah%20Loh%20Abdullah.pdf |