메뉴 건너뛰기




Volumn , Issue , 2012, Pages 109-118

Comparing the performance of fault prediction models which report multiple performance measures: Recomputing the confusion matrix

Author keywords

Confusion matrix; Fault; Machine learning

Indexed keywords

CONFUSION MATRICES; FAULT; FAULT PREDICTION; PERFORMANCE MEASURE; PREDICTIVE PERFORMANCE; RE-COMPUTING;

EID: 84867733834     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2365324.2365338     Document Type: Conference Paper
Times cited : (43)

References (36)
  • 2
    • 71649110371 scopus 로고    scopus 로고
    • A systematic and comprehensive investigation of methods to build and evaluate fault prediction models
    • E. Arisholm, L. C. Briand, and E. B. Johannessen. A systematic and comprehensive investigation of methods to build and evaluate fault prediction models. Journal of Systems and Software, 83(1):2-17, 2010.
    • (2010) Journal of Systems and Software , vol.83 , Issue.1 , pp. 2-17
    • Arisholm, E.1    Briand, L.C.2    Johannessen, E.B.3
  • 3
    • 0033931867 scopus 로고    scopus 로고
    • Assessing the accuracy of prediction algorithms for classification: An overview
    • P. Baldi, S. Brunak, Y. Chauvin, C. Andersen, and H. Nielsen. Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics, 16(5):412-424, 2000.
    • (2000) Bioinformatics , vol.16 , Issue.5 , pp. 412-424
    • Baldi, P.1    Brunak, S.2    Chauvin, Y.3    Andersen, C.4    Nielsen, H.5
  • 4
    • 27144531570 scopus 로고    scopus 로고
    • A study of the behavior of several methods for balancing machine learning training data
    • G. Batista, R. Prati, and M. Monard. A study of the behavior of several methods for balancing machine learning training data. ACM SIGKDD Explorations Newsletter, 6(1):20-29, 2004.
    • (2004) ACM SIGKDD Explorations Newsletter , vol.6 , Issue.1 , pp. 20-29
    • Batista, G.1    Prati, R.2    Monard, M.3
  • 5
    • 84867693175 scopus 로고    scopus 로고
    • Recomputing the confusion matrix for prediction studies reporting categorical output
    • D. Bowes and D. Gray. Recomputing the confusion matrix for prediction studies reporting categorical output. Technical Report 509, University of Hertfordshire, 2011.
    • (2011) Technical Report 509, University of Hertfordshire
    • Bowes, D.1    Gray, D.2
  • 7
    • 27144549260 scopus 로고    scopus 로고
    • Editorial: Special issue on learning from imbalanced data sets
    • N. V. Chawla, N. Japkowicz, and A. Kotcz. Editorial: special issue on learning from imbalanced data sets. SIGKDD Explorations, 6(1):1-6, 2004.
    • (2004) SIGKDD Explorations , vol.6 , Issue.1 , pp. 1-6
    • Chawla, N.V.1    Japkowicz, N.2    Kotcz, A.3
  • 8
    • 79952446954 scopus 로고    scopus 로고
    • Research synthesis in software engineering: A tertiary study
    • May
    • D. S. Cruzes and T. Dybå. Research synthesis in software engineering: A tertiary study. Inf. Softw. Technol., 53:440-455, May 2011.
    • (2011) Inf. Softw. Technol. , vol.53 , pp. 440-455
    • Cruzes, D.S.1    Dybå, T.2
  • 10
    • 77549086028 scopus 로고    scopus 로고
    • A symbolic fault-prediction model based on multiobjective particle swarm optimization
    • A. B. de Carvalho, A. Pozo, and S. R. Vergilio. A symbolic fault-prediction model based on multiobjective particle swarm optimization. Journal of Systems and Software, 83(5):868-882, 2010.
    • (2010) Journal of Systems and Software , vol.83 , Issue.5 , pp. 868-882
    • De Carvalho, A.B.1    Pozo, A.2    Vergilio, S.R.3
  • 12
    • 40749135790 scopus 로고    scopus 로고
    • Predicting defect-prone software modules using support vector machines
    • K. O. Elish and M. O. Elish. Predicting defect-prone software modules using support vector machines. Journal of Systems and Software, 81(5):649 - 660, 2008.
    • (2008) Journal of Systems and Software , vol.81 , Issue.5 , pp. 649-660
    • Elish, K.O.1    Elish, M.O.2
  • 16
    • 52549091028 scopus 로고    scopus 로고
    • Techniques for evaluating fault prediction models
    • Y. Jiang, B. Cukic, and Y. Ma. Techniques for evaluating fault prediction models. Empirical Software Engineering, 13(5):561-595, 2008.
    • (2008) Empirical Software Engineering , vol.13 , Issue.5 , pp. 561-595
    • Jiang, Y.1    Cukic, B.2    Ma, Y.3
  • 19
    • 3543063465 scopus 로고    scopus 로고
    • Comparative assessment of software quality classification techniques: An empirical case study
    • T. Khoshgoftaar and N. Seliya. Comparative assessment of software quality classification techniques: An empirical case study. Empirical Software Engineering, 9(3):229-257, 2004.
    • (2004) Empirical Software Engineering , vol.9 , Issue.3 , pp. 229-257
    • Khoshgoftaar, T.1    Seliya, N.2
  • 20
    • 28244461468 scopus 로고    scopus 로고
    • Building effective defect-prediction models in practice
    • IEEE, nov.-dec.
    • A. Koru and H. Liu. Building effective defect-prediction models in practice. Software, IEEE, 22(6):23 - 29, nov.-dec. 2005.
    • (2005) Software , vol.22 , Issue.6 , pp. 23-29
    • Koru, A.1    Liu, H.2
  • 22
    • 49349089233 scopus 로고    scopus 로고
    • Benchmarking classification models for software defect prediction: A proposed framework and novel findings
    • july-aug.
    • S. Lessmann, B. Baesens, C. Mues, and S. Pietsch. Benchmarking classification models for software defect prediction: A proposed framework and novel findings. Software Engineering, IEEE Transactions on, 34(4):485 -496, july-aug. 2008.
    • (2008) Software Engineering, IEEE Transactions on , vol.34 , Issue.4 , pp. 485-496
    • Lessmann, S.1    Baesens, B.2    Mues, C.3    Pietsch, S.4
  • 24
    • 34548245485 scopus 로고    scopus 로고
    • Problems with precision: A response to comments on 'data mining static code attributes to learn defect predictors'
    • sept.
    • T. Menzies, A. Dekhtyar, J. Distefano, and J. Greenwald. Problems with precision: A response to "comments on 'data mining static code attributes to learn defect predictors'". Software Engineering, IEEE Transactions on, 33(9):637 -640, sept. 2007.
    • (2007) Software Engineering, IEEE Transactions on , vol.33 , Issue.9 , pp. 637-640
    • Menzies, T.1    Dekhtyar, A.2    Distefano, J.3    Greenwald, J.4
  • 27
    • 34648835118 scopus 로고    scopus 로고
    • Empirical analysis of software fault content and fault proneness using bayesian methods
    • oct.
    • G. Pai and J. Dugan. Empirical analysis of software fault content and fault proneness using bayesian methods. Software Engineering, IEEE Transactions on, 33(10):675 -686, oct. 2007.
    • (2007) Software Engineering, IEEE Transactions on , vol.33 , Issue.10 , pp. 675-686
    • Pai, G.1    Dugan, J.2
  • 30
    • 67349201689 scopus 로고    scopus 로고
    • Using pre & post-processing methods to improve binding site predictions
    • Y. Sun, C. Castellano, M. Robinson, R. Adams, A. Rust, and N. Davey. Using pre & post-processing methods to improve binding site predictions. Pattern Recognition, 42(9):1949-1958, 2009.
    • (2009) Pattern Recognition , vol.42 , Issue.9 , pp. 1949-1958
    • Sun, Y.1    Castellano, C.2    Robinson, M.3    Adams, R.4    Rust, A.5    Davey, N.6
  • 31
    • 64049099247 scopus 로고    scopus 로고
    • Data mining source code for locating software bugs: A case study in telecommunication industry
    • B. Turhan, G. Kocak, and A. Bener. Data mining source code for locating software bugs: A case study in telecommunication industry. Expert Systems with Applications, 36(6):9986-9990, 2009.
    • (2009) Expert Systems with Applications , vol.36 , Issue.6 , pp. 9986-9990
    • Turhan, B.1    Kocak, G.2    Bener, A.3
  • 33
    • 78649782445 scopus 로고    scopus 로고
    • Evolutionary optimization of software quality modeling with multiple repositories
    • L. Yi, T. M. Khoshgoftaar, and N. Seliya. Evolutionary optimization of software quality modeling with multiple repositories. Software Engineering, IEEE Transactions on, 36(6):852-864, 2010.
    • (2010) Software Engineering, IEEE Transactions on , vol.36 , Issue.6 , pp. 852-864
    • Yi, L.1    Khoshgoftaar, T.M.2    Seliya, N.3
  • 35
    • 34548253429 scopus 로고    scopus 로고
    • Comments on data mining static code attributes to learn defect predictors
    • sept.
    • H. Zhang and X. Zhang. Comments on "data mining static code attributes to learn defect predictors". Software Engineering, IEEE Transactions on, 33(9):635 -637, sept. 2007.
    • (2007) Software Engineering, IEEE Transactions on , vol.33 , Issue.9 , pp. 635-637
    • Zhang, H.1    Zhang, X.2
  • 36
    • 33947174112 scopus 로고    scopus 로고
    • Empirical analysis of object-oriented design metrics for predicting high and low severity faults Software Engineering
    • oct.
    • Y. Zhou and H. Leung. Empirical analysis of object-oriented design metrics for predicting high and low severity faults. Software Engineering, IEEE Transactions on, 32(10):771 -789, oct. 2006.
    • (2006) IEEE Transactions on , vol.32 , Issue.10 , pp. 771-789
    • Zhou, Y.1    Leung, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.