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Volumn , Issue , 2004, Pages 234-241

Feature selection using linear classifier weights: Interaction with classification models

Author keywords

Feature scoring; Feature selection; Information retrieval; Linear SVM; SVM normal; Text classification; Vector representation

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA PROCESSING; LEARNING ALGORITHMS; LINGUISTICS; MATHEMATICAL MODELS; OPTIMIZATION; VECTORS;

EID: 8644274789     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (174)

References (11)
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    • A comparison of event models for Naïve Bayes text categorization
    • AAAI Press
    • Andrew McCallum and Kamal Nigam. A comparison of event models for Naïve Bayes text categorization. AAAI Workshop on Learning for Text Categorization (pp. 41-48). AAAI Press, 1998.
    • (1998) AAAI Workshop on Learning for Text Categorization , pp. 41-48
    • McCallum, A.1    Nigam, K.2
  • 6
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    • Feature selection for unbalanced class distribution and Naïve Bayes
    • San Francisco: Morgan Kaufmann
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    • Mladenic, D.1    Grobelnik, M.2
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    • Frank Rosenblatt. The Perceptron: A probabilistic model for information storage and organization in the brain. Psych. Review 65(6), 386-408. Reprinted in: J. A. D. Anderson, E. Rosenfeld (Eds.), Neurocomputing: foundations of research. Cambridge, MA: MIT Press, 1988.
    • (1988) Psych. Review , vol.65 , Issue.6 , pp. 386-408
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  • 9
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    • Information theoretic feature crediting in multiclass Support Vector Machines
    • Chicago, IL, USA, April 5-7, 2001. SIAM
    • Vikas Sindhwani, Pushpak Bhattacharya, and Subrata Rakshit. Information theoretic feature crediting in multiclass Support Vector Machines. 1st SIAM Int. Conf. on Data Mining (SDM 2001), Chicago, IL, USA, April 5-7, 2001. SIAM, 2001.
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    • Sindhwani, V.1    Bhattacharya, P.2    Rakshit, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.