Cover Image

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...

Full description

Saved in:
Bibliographic Details
Main Author: Latifah Loh, Abdullah
Format: Thesis
Language:English
Published: Faculty of Computer Science and Information Technology 2007
Subjects:
T Technology (General)
Online Access:http://ir.unimas.my/id/eprint/1714/2/Latifah%20Loh%20Abdullah.pdf
http://ir.unimas.my/id/eprint/1714/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimas.ir.1714
record_format eprints
spelling my.unimas.ir.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).
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Latifah Loh, Abdullah
The effect of term weighting measures on feature selection
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.
format Thesis
author Latifah Loh, Abdullah
author_facet Latifah Loh, Abdullah
author_sort Latifah Loh, Abdullah
title The effect of term weighting measures on feature selection
title_short 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_sort effect of term weighting measures on feature selection
publisher Faculty of Computer Science and Information Technology
publishDate 2007
url http://ir.unimas.my/id/eprint/1714/2/Latifah%20Loh%20Abdullah.pdf
http://ir.unimas.my/id/eprint/1714/
_version_ 1761623518323146752
score 13.211869

Similar Items