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Volumn 21, Issue 1, 2004, Pages 57-79

Instance-based regression by partitioning feature projections

Author keywords

Feature projections; Machine learning; Regression

Indexed keywords

ALGORITHMS; COMPUTER OPERATING SYSTEMS; DATA REDUCTION; DECISION THEORY; LEAST SQUARES APPROXIMATIONS; REGRESSION ANALYSIS;

EID: 3543063984     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:APIN.0000027767.87895.b2     Document Type: Article
Times cited : (10)

References (26)
  • 1
    • 0004679071 scopus 로고    scopus 로고
    • An overview of regression techniques for knowledge discovery
    • Cambridge University Press
    • I. Uysal and H.A. Güvenir, "An overview of regression techniques for knowledge discovery," Knowledge Engineering Review, Cambridge University Press, vol. 14, pp. 1-22, 1999.
    • (1999) Knowledge Engineering Review , vol.14 , pp. 1-22
    • Uysal, I.1    Güvenir, H.A.2
  • 2
    • 0031073477 scopus 로고    scopus 로고
    • A review and empirical evaluation of feature-weighting methods for a class of lazy learning algorithms
    • D. Wettschereck, D.W. Aha, and T. Mohri, T. "A review and empirical evaluation of feature-weighting methods for a class of lazy learning algorithms," AI Review, vol. 11, pp. 273-314, 1997.
    • (1997) AI Review , vol.11 , pp. 273-314
    • Wettschereck, D.1    Aha, D.W.2    Mohri, T.3
  • 3
    • 0030130153 scopus 로고    scopus 로고
    • Classification by feature partitioning
    • H.A. Güvenir and I. Sirin, "Classification by feature partitioning," Machine Learning, vol. 23, pp. 47-67, 1996.
    • (1996) Machine Learning , vol.23 , pp. 47-67
    • Güvenir, H.A.1    Sirin, I.2
  • 5
    • 0032127185 scopus 로고    scopus 로고
    • Learning differential diagnosis of erythemato squamous diseases using voting feature intervals
    • H.A. Güvenir, G. Demiroz, and H. Iiter. "Learning differential diagnosis of erythemato squamous diseases using voting feature intervals," Artificial Intelligence in Medicine, vol. 13, pp. 147-165, 1998.
    • (1998) Artificial Intelligence in Medicine , vol.13 , pp. 147-165
    • Güvenir, H.A.1    Demiroz, G.2    Iiter, H.3
  • 6
    • 0003408496 scopus 로고    scopus 로고
    • University of California, Department of Information and Computer Science, Irvine, CA
    • C. Blake, E. Keogh, and C.J. Merz, "UCI repository of machine learning databases," [http://www.ics.uci.edu/mleam/MLRepository.html], University of California, Department of Information and Computer Science, Irvine, CA, 1998.
    • (1998) UCI Repository of Machine Learning Databases
    • Blake, C.1    Keogh, E.2    Merz, C.J.3
  • 7
    • 0027580356 scopus 로고
    • Very simple classification rules perform well on most commonly used datasets
    • R.C. Holte, "Very simple classification rules perform well on most commonly used datasets," Machine Learning, vol. 1, pp. 63-91, 1993.
    • (1993) Machine Learning , vol.1 , pp. 63-91
    • Holte, R.C.1
  • 8
    • 0000846313 scopus 로고
    • Rule-based machine learning methods for functional prediction
    • S. Weiss and N. Indurkhya, "Rule-based machine learning methods for functional prediction," Journal of Artificial Intelligence Research, vol. 3, pp. 383-403, 1995.
    • (1995) Journal of Artificial Intelligence Research , vol.3 , pp. 383-403
    • Weiss, S.1    Indurkhya, N.2
  • 12
    • 0002432565 scopus 로고
    • Multivariate adaptive regression splines
    • J.H. Friedman, "Multivariate adaptive regression splines," The Annals of Statistics, vol. 19, pp. 1-141, 1991.
    • (1991) The Annals of Statistics , vol.19 , pp. 1-141
    • Friedman, J.H.1
  • 15
    • 21744462998 scopus 로고    scopus 로고
    • On bias, variance, 0/1-loss and the curse of dimensionality
    • J.H. Friedman, "On bias, variance, 0/1-loss and the curse of dimensionality," Data Mining and Knowledge Discovery, vol. 1, pp. 55-77, 1997.
    • (1997) Data Mining and Knowledge Discovery , vol.1 , pp. 55-77
    • Friedman, J.H.1
  • 16
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • L. Breiman, L. "Bagging predictors," Machine Learning, vol. 24, pp. 123-140, 1996.
    • (1996) Machine Learning , vol.24 , pp. 123-140
    • Breiman, L.1
  • 21
    • 3543118170 scopus 로고
    • Datasets and stories: Introduction and guidelines
    • [Online]
    • R.H. Lock and T. Arnold, "Datasets and stories: Introduction and guidelines," Journal of Statistics Education [Online], vol. 1, [http://www.amstat.org/publications/jse/v1n1/datasets.html], 1993.
    • (1993) Journal of Statistics Education , vol.1
    • Lock, R.H.1    Arnold, T.2
  • 22
    • 3543120431 scopus 로고    scopus 로고
    • SPSS, "Sample data sets," [ftp://ftp.spss.com/pub/spss/sample/ datasets/], 1999.
    • (1999) Sample Data Sets
  • 25
    • 85166350822 scopus 로고    scopus 로고
    • Occam's two razors, the sharp and the blunt
    • P. Domingos, "Occam's two razors, the sharp and the blunt," in Proc. KDD'98, 1998.
    • (1998) Proc. KDD'98
    • Domingos, P.1
  • 26
    • 0029679031 scopus 로고    scopus 로고
    • Further experimental evidence against the utility of Occam's razor
    • G. Webb and M. Kuzmycz, "Further experimental evidence against the utility of Occam's razor," Journal of Artificial Intelligence Research, vol. 4, pp. 397-417, 1996.
    • (1996) Journal of Artificial Intelligence Research , vol.4 , pp. 397-417
    • Webb, G.1    Kuzmycz, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.