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» Combining feature selectors for text classification
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CIKM
2006
Springer
13 years 8 months ago
Combining feature selectors for text classification
We introduce several methods of combining feature selectors for text classification. Results from a large investigation of these combinations are summarized. Easily constructed co...
J. Scott Olsson, Douglas W. Oard
DEXAW
2010
IEEE
190views Database» more  DEXAW 2010»
13 years 1 months ago
A Comparison of Stylometric and Lexical Features for Web Genre Classification and Emotion Classification in Blogs
In the blogosphere, the amount of digital content is expanding and for search engines, new challenges have been imposed. Due to the changing information need, automatic methods are...
Elisabeth Lex, Andreas Juffinger, Michael Granitze...
CANDC
2005
ACM
13 years 4 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 5 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
ACL
2009
13 years 2 months ago
A Framework of Feature Selection Methods for Text Categorization
In text categorization, feature selection (FS) is a strategy that aims at making text classifiers more efficient and accurate. However, when dealing with a new task, it is still d...
Shoushan Li, Rui Xia, Chengqing Zong, Chu-Ren Huan...