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Volumn 2006, Issue , 2006, Pages 574-579

Machine learning for imbalanced datasets: Application in medical diagnostic

Author keywords

Accuracy; Imbalanced datasets; Machine learning; Medical diagnosis; Validity and comprchensibility

Indexed keywords

ALGORITHMS; CARDIOVASCULAR SURGERY; CLASSIFICATION (OF INFORMATION); DATABASE SYSTEMS; DIAGNOSIS; NEURAL NETWORKS;

EID: 33746095421     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (65)

References (13)
  • 2
    • 20444392475 scopus 로고    scopus 로고
    • Using random forest to learn imbalanced data
    • Statistics Department, University of California at Berkeley
    • Chen, C.; Liaw, A.; and Breiman, L. 2004. Using Random Forest to Learn Imbalanced Data. Technical report 666, Statistics Department, University of California at Berkeley.
    • (2004) Technical Report , vol.666
    • Chen, C.1    Liaw, A.2    Breiman, L.3
  • 7
    • 0034922742 scopus 로고    scopus 로고
    • Machine learning for medical diagnosis: History, state of the art and perspective, invited paper
    • ISSN 0933-3657
    • Kononenko, I. 2001. Machine Learning for Medical Diagnosis: History, State of the Art and Perspective, Invited paper. Artificial Intelligence in Medicine - ISSN 0933-3657 23(1):89-109.
    • (2001) Artificial Intelligence in Medicine , vol.23 , Issue.1 , pp. 89-109
    • Kononenko, I.1
  • 9
    • 0025649758 scopus 로고
    • Ambulalory blood pressure monitoring: Research and clinical applications
    • Mancia, G. 1990. Ambulalory Blood Pressure Monitoring: Research and Clinical Applications. Journal of Hypertension (Suppl 7): S1-S13.
    • (1990) Journal of Hypertension , Issue.7 SUPPL.
    • Mancia, G.1
  • 10
    • 18844396779 scopus 로고    scopus 로고
    • A reliable index for the prognostic significance of blood pressure variability
    • Mena, L; Pintos, S.; Queipo, N.; Aizpurua, J.; el al. 2005. A Reliable Index for the Prognostic Significance of Blood Pressure Variability. Journal of Hypertension 23:505-512.
    • (2005) Journal of Hypertension , vol.23 , pp. 505-512
    • Mena, L.1    Pintos, S.2    Queipo, N.3    Aizpurua, J.4
  • 11
    • 0003408496 scopus 로고
    • UCI repository of machine learning databases [machine-readable data repositoty]
    • University of California, Irvine
    • Murphy, P.; and Aha, D. 1994. UCI Repository of Machine Learning Databases [machine-readable data repositoty]. Technical Report, University of California, Irvine.
    • (1994) Technical Report
    • Murphy, P.1    Aha, D.2
  • 12
    • 0004322632 scopus 로고    scopus 로고
    • Sequential minimal optimisation: A fast algorithm for training support vector machines
    • Microsoft Research
    • Platt, J.C. 1998. Sequential Minimal Optimisation: A Fast Algorithm for Training Support Vector Machines, Technical Report MSR-TR-98-14, Microsoft Research.
    • (1998) Technical Report , vol.MSR-TR-98-14
    • Platt, J.C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.