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Volumn 04-08-April-2016, Issue , 2016, Pages 1486-1491

A meta-learning framework for algorithm recommendation in software fault prediction

Author keywords

Algorithm recommendation; Machine learning; Meta learning; Software fault prediction; Software quality

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SOFTWARE SELECTION AND EVALUATION; FORECASTING; LEARNING SYSTEMS; QUALITY ASSURANCE; RECOMMENDER SYSTEMS;

EID: 84975873980     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2851613.2851788     Document Type: Conference Paper
Times cited : (18)

References (19)
  • 4
    • 0037361994 scopus 로고    scopus 로고
    • Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results
    • Mar.
    • P. B. Brazdil, C. Soares, and J. P. D. Costa. Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results. Machine Learning, 50(3):251-277, Mar. 2003.
    • (2003) Machine Learning , vol.50 , Issue.3 , pp. 251-277
    • Brazdil, P.B.1    Soares, C.2    Costa, J.P.D.3
  • 5
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman. Random forests. Machine Learning, 45(1):5-32, 2001.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 6
    • 0035152294 scopus 로고    scopus 로고
    • Comparing case-based reasoning classifiers for predicting high risk software components
    • K. El Emam, S. Benlarbi, N. Goel, and S. N. Rai. Comparing case-based reasoning classifiers for predicting high risk software components. Journal of Systems and Software, 55(3):301-320, 2001.
    • (2001) Journal of Systems and Software , vol.55 , Issue.3 , pp. 301-320
    • El Emam, K.1    Benlarbi, S.2    Goel, N.3    Rai, S.N.4
  • 14
    • 49349089233 scopus 로고    scopus 로고
    • Benchmarking classification models for software defect prediction: A proposed framework and novel findings
    • July
    • S. Lessmann, B. Baesens, C. Mues, and S. Pietsch. Benchmarking classification models for software defect prediction: A proposed framework and novel findings. IEEE Transactions on Software Engineering, 34(4):485-496, July 2008.
    • (2008) IEEE Transactions on Software Engineering , vol.34 , Issue.4 , pp. 485-496
    • Lessmann, S.1    Baesens, B.2    Mues, C.3    Pietsch, S.4
  • 15
    • 84919754115 scopus 로고    scopus 로고
    • A systematic review of machine learning techniques for software fault prediction
    • Complete
    • R. Malhotra. A systematic review of machine learning techniques for software fault prediction. Applied Soft Computing, 27(Complete):504-518, 2015.
    • (2015) Applied Soft Computing , vol.27 , pp. 504-518
    • Malhotra, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.