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Abstract: Text categorization is useful for indexing documents for information retrieval, filtering parts for document understanding, and summarizing contents of documents of special interests. We describe a text categorization task and an experiment using documents from the Reuters and OHSUMED collections. We applied the Decision Forest classifier and compared its accuracies to those of C4.5 and kNN classifiers, using both category dependent and category independent term selection schemes. It is found... (Update)
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BibTeX entry: (Update)
Chen, H. & Ho, T.K.: Evaluation of decision forests on text categorization. In: Proc. 7th SPIE Conference on Document Recognition and Retrieval (2000) 191-199 http://citeseer.ist.psu.edu/article/chen00evaluation.html More
@inproceedings{ chen00evaluation,
author = "Hao Chen and Tin Kam Ho",
title = "Evaluation of Decision Forests on Text Categorization",
booktitle = "Proceedings of the 7th {SPIE} Conference on Document Recognition and Retrieval",
publisher = "SPIE - The International Society for Optical Engineering",
address = "San Jose, US",
editor = "Daniel P. Lopresti and Jiangying Zhou",
pages = "191--199",
year = "2000",
url = "citeseer.ist.psu.edu/article/chen00evaluation.html" }
Citations (may not include all citations):2177 Programs for Machine Learning (context) - Quinlan - 1993
215 A comparative study on feature selection in text categorizat.. - Yang, Pedersen - 1997
149 An evaluation of statistical approaches to text categorizati.. - Yang - 1997
123 A vector space model for automatic indexing (context) - Salton, Wong et al. - 1975
97 Comparison of two learning algorithms for text categorizatio.. - Lewis, Ringuette - 1994
82 Information Retrieval: Data Structures & Algorithms (context) - Frakes, Baeza-Yates - 1992
59 A neural network approach to topic spotting - Wiener, Pedersen et al. - 1995
49 The random subspace method for constructing decision forests - Ho - 1998
44 An example-based mapping method for text categorization and .. (context) - Yang, Chute - 1994
37 Representation and Learning in Information Retrieval (context) - Lewis - 1992
27 Towards language independent automated learning of text cate.. - Apte, Damerau et al. - 1994
14 a rule-based multistage indexing systems for large subject e.. (context) - Fuhr, Hartmanna et al. - 1991
2 Itp interpretext system: Muc-3 test results and analysis (context) - Dahlgren, Lord et al. - 1991
1 Training algorithms for lineare text classiers (context) - Lewis, Schapire et al. - 1996
1 in AAAI-88 Workshop on Plan Recognition (context) - Hardt, planned - 1988
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