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Volumn , Issue , 2005, Pages 4-7

Making logistic regression a core data mining tool with TR-IRLS

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATABASE SYSTEMS; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; REAL TIME SYSTEMS; REGRESSION ANALYSIS;

EID: 34548559277     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2005.90     Document Type: Conference Paper
Times cited : (39)

References (21)
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    • C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/ libsvm.
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    • Chang, C.-C.1    Lin, C.-J.2
  • 2
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  • 5
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    • SAS. http://www.sas.com
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  • 7
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    • Logistic Regression for Data Mining and High-Dimensional Classification. Technical Report TR-O4-34, Robotics Inst., Carnegie Mellon Univ., Pgh, PA
    • May
    • P. Komarek. Logistic Regression for Data Mining and High-Dimensional Classification. Technical Report TR-O4-34, Robotics Inst., Carnegie Mellon Univ., Pgh, PA, May 2004.
    • (2004)
    • Komarek, P.1
  • 8
    • 34548558244 scopus 로고    scopus 로고
    • P. Komarek. Making Logistic Regression A Core Data Mining Tool: A Practical Investigation of Accuracy, Speed, and Simplicity. Technical Report TR-O5-27, Robotics Inst., Carnegie Mellon Univ., Pgh, PA, May 2004.
    • P. Komarek. Making Logistic Regression A Core Data Mining Tool: A Practical Investigation of Accuracy, Speed, and Simplicity. Technical Report TR-O5-27, Robotics Inst., Carnegie Mellon Univ., Pgh, PA, May 2004.
  • 10
    • 33745387399 scopus 로고    scopus 로고
    • Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs
    • P. Komarek and A. Moore. Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs. In Artificial Intelligence and Statistics, 2003.
    • (2003) Artificial Intelligence and Statistics
    • Komarek, P.1    Moore, A.2
  • 14
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    • Fitting Linear Models: An Application of Conjugate Gradient Algorithms
    • of, Springer-Verlag, New York
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    • (1982) Lecture Notes in Statistics , vol.10
    • McIntosh, A.1
  • 15
    • 0012352869 scopus 로고    scopus 로고
    • Algorithms for maximum-likelihood logistic regression
    • Carnegie Mellon University, October
    • T. P. Minka. Algorithms for maximum-likelihood logistic regression. Technical Report Stats 758, Carnegie Mellon University, October 2001.
    • (2001) Technical Report Stats , vol.758
    • Minka, T.P.1
  • 19
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    • An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
    • Technical Report CS-94-125, Carnegie Mellon University, Pittsburgh
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  • 21
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    • Kernel logistic regression and the import vector machine
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    • J. Zhu and T. Hastie. Kernel logistic regression and the import vector machine. Journal of Computational and Graphical Statistics, 14(1): 185-205, March 2005.
    • (2005) Journal of Computational and Graphical Statistics , vol.14 , Issue.1 , pp. 185-205
    • Zhu, J.1    Hastie, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.