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Volumn 14, Issue 4, 2008, Pages 297-307

ProICET: A cost-sensitive system for prostate cancer data

Author keywords

Cost sensitive learning; Data mining; Hybrid algorithm; Implementation; Prostate cancer

Indexed keywords

BIOMEDICINE; CANCER CLASSIFICATION; CONFERENCE PAPER; COST BENEFIT ANALYSIS; DATA ANALYSIS; DATA MINING; GENETIC ALGORITHM; INFORMATION PROCESSING; KNOWLEDGE; LEARNING ALGORITHM; MEDICAL INFORMATION SYSTEM; PROSTATE CANCER;

EID: 56049113949     PISSN: 14604582     EISSN: 17412811     Source Type: Journal    
DOI: 10.1177/1460458208096558     Document Type: Conference Paper
Times cited : (4)

References (18)
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    • Freund, Y.1    Schapire, R.2
  • 9
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    • Hybrid cost-sensitive decision tree
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    • Sheng, S.1    Ling, C.2
  • 10
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    • Simple test strategies for cost-sensitive decision trees
    • Sheng S., Ling C., Yang Q. Simple test strategies for cost-sensitive decision trees. ECML 2005; 365-76.
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    • Sheng, S.1    Ling, C.2    Yang, Q.3
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    • Enhancing classifiers through neural network ensembles
    • In 6-8 September, Cluj-Napoca, Romania
    • Onaci A., Vidrighin C., Cuibus M., Potolea R. Enhancing classifiers through neural network ensembles. In Proceedings of the 3rd ICCP 2007, 6-8 September, Cluj-Napoca, Romania, pp. 57-64.
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    • Onaci, A.1    Vidrighin, C.2    Cuibus, M.3    Potolea, R.4
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    • Improving classification performance on real data through imputation
    • In 22-25 May, Cluj-Napoca
    • Vidrighin C., Muresan T., Potolea R. Improving classification performance on real data through imputation. In Proceedings of AQTR 2008, 22-25 May, Cluj-Napoca, pp. 464-70.
    • Proceedings of AQTR 2008 , pp. 464-470
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.