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Volumn 4491 LNCS, Issue PART 1, 2007, Pages 1310-1317

A probabilistic approach to feature selection for multi-class text categorization

Author keywords

[No Author keywords available]

Indexed keywords

PROBABILITY; TEXT PROCESSING; THEOREM PROVING;

EID: 37249061676     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-72383-7_153     Document Type: Conference Paper
Times cited : (9)

References (13)
  • 7
    • 0002442796 scopus 로고    scopus 로고
    • Machine Learning in Automated Text Categorization
    • Sebastiani, F.: Machine Learning in Automated Text Categorization. ACM computing Surveys 34 (1) (2002) 1-47
    • (2002) ACM computing Surveys , vol.34 , Issue.1 , pp. 1-47
    • Sebastiani, F.1
  • 9
    • 0036161259 scopus 로고    scopus 로고
    • Gene Selection for Cancer Classification Using Support Vector Machines
    • Guyon, I., Weston, J., Barnhill, S., Vapnik, V.: Gene Selection for Cancer Classification Using Support Vector Machines. Machine Learning 46 (2002) 389-422
    • (2002) Machine Learning , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 10
    • 35048828418 scopus 로고    scopus 로고
    • Feature Selection for Fast Image Classification with Support Vector Machines
    • Proc. ICONIP
    • Fan, Z.G., Wang, K.A., Lu, B.L.: Feature Selection for Fast Image Classification with Support Vector Machines. Proc. ICONIP 2004, LNCS, 3316 (2004) 711-720
    • (2004) LNCS , vol.3316 , pp. 711-720
    • Fan, Z.G.1    Wang, K.A.2    Lu, B.L.3
  • 11
    • 0038647814 scopus 로고    scopus 로고
    • Hierarchical Classification Andfeature Reduction for Fast Face Detection with Support Vector Machines
    • Heisele, B., Serre, T., Prentice, S., Poggio, T.: Hierarchical Classification Andfeature Reduction for Fast Face Detection with Support Vector Machines. Pattern Recognition 36(2003) 2007-2017
    • (2003) Pattern Recognition , vol.36 , pp. 2007-2017
    • Heisele, B.1    Serre, T.2    Prentice, S.3    Poggio, T.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.