메뉴 건너뛰기




Volumn 9, Issue 2, 2005, Pages 175-188

Optimal bin number for equal frequency discretizations in supervized learning

Author keywords

bayesianism; data analysis; data mining; discretization; machine learning

Indexed keywords

BAYESIAN NETWORKS; DATA REDUCTION; DISCRETE EVENT SIMULATION; LEARNING SYSTEMS; MACHINE LEARNING; VOLUME MEASUREMENT;

EID: 41749102443     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/ida-2005-9204     Document Type: Conference Paper
Times cited : (32)

References (21)
  • 1
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • H. Akaike, A new look at the statistical model identification, IEEE Transactions on Automatic Control 19 (1974), 716-723.
    • (1974) IEEE Transactions on Automatic Control , vol.19 , pp. 716-723
    • Akaike, H.1
  • 3
    • 0003408496 scopus 로고    scopus 로고
    • Irvine, CA University of California Department of Information and Computer Science
    • C.L. Blake and C.J. Merz, UCI Repository of machine learning databases (www.ics.uci.edu/?mlearn/MLRepository. html), Irvine, CA: University of California, Department of Information and Computer Science, 1998.
    • (1998) UCI Repository of Machine Learning Databases
    • Blake, C.L.1    Merz, C.J.2
  • 6
    • 0002823280 scopus 로고
    • On changing continuous attributes into ordered discrete attributes
    • Springer-Verlag
    • J. Catlett, On Changing Continuous Attributes into ordered discrete Attributes, In Proceedings of the European Working Session on Learning, Springer-Verlag, 1991, pp. 87-102.
    • (1991) Proceedings of the European Working Session on Learning , pp. 87-102
    • Catlett, J.1
  • 9
    • 0003024008 scopus 로고
    • On the handling of continuous-valued attributes in decision tree generation
    • U. Fayyad and K. Irani, On the handling of continuous-valued attributes in decision tree generation, Machine Learning 8 (1992), 87-102.
    • (1992) Machine Learning , vol.8 , pp. 87-102
    • Fayyad, U.1    Irani, K.2
  • 10
    • 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 11 (1993), 63-90.
    • (1993) Machine Learning , vol.11 , pp. 63-90
    • Holte, R.C.1
  • 11
    • 0000661829 scopus 로고
    • An explanatory technique for investigating large quantities of categorical data
    • G.V. Kass, An explanatory technique for investigating large quantities of categorical data, Applied statistics 29(2) (1980), 119-127.
    • (1980) Applied Statistics , vol.29 , Issue.2 , pp. 119-127
    • Kass, G.V.1
  • 16
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • J. Rissanen, Modeling by shortest data description, Automatica 14 (1978), 465-471.
    • (1978) Automatica , vol.14 , pp. 465-471
    • Rissanen, J.1
  • 17
    • 0001098776 scopus 로고
    • A universal prior for integers and estimation by minimum description length
    • J. Rissanen, A universal prior for integers and estimation by minimum description length, Ann. Statist. 11 (1983), 416-431.
    • (1983) Ann. Statist , vol.11 , pp. 416-431
    • Rissanen, J.1
  • 18
    • 0000216844 scopus 로고
    • Averaged shifted histograms: Effective nonparametric density estimators in several dimensions
    • D.W. Scott, Averaged shifted histograms: Effective nonparametric density estimators in several dimensions, Ann. Statist. 13 (1979), 1024-1040.
    • (1979) Ann. Statist , vol.13 , pp. 1024-1040
    • Scott, D.W.1
  • 19
    • 84941185462 scopus 로고
    • The choice of a class interval
    • H.A. Sturges, The choice of a class interval, J. Am. Stat. Assoc 21 (1926), 65-66.
    • (1926) J. Am. Stat. Assoc , vol.21 , pp. 65-66
    • Sturges, H.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.