메뉴 건너뛰기




Volumn 2006, Issue , 2006, Pages 929-934

Maximum profit mining and its application in software development

Author keywords

Cost sensitive learning; Data mining; Escalation prediction

Indexed keywords

COMPUTER DEBUGGING; COMPUTER SOFTWARE MAINTENANCE; DATA MINING; DECISION SUPPORT SYSTEMS; LEARNING SYSTEMS; TREES (MATHEMATICS);

EID: 33749562833     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1150402.1150530     Document Type: Conference Paper
Times cited : (16)

References (22)
  • 3
    • 0004285392 scopus 로고
    • Prentice-Hall Advances in Computing Science & Technology Series
    • Boehm, B.W. 1981. Software Engineering Economics. Prentice-Hall Advances in Computing Science & Technology Series.
    • (1981) Software Engineering Economics
    • Boehm, B.W.1
  • 4
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman, L. 1996. Bagging Predictors. Machine Learning 24(2): 123-140.
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 5
    • 33749577396 scopus 로고    scopus 로고
    • The business impact of predictive analytics
    • (forthcoming). Book chapter. Zhu, Q, and Davidson, I., editors. Idea Group Publishing, Hershey, PA
    • Bruckhaus, T. 2006 (forthcoming). The Business Impact of Predictive Analytics. Book chapter in Knowledge Discovery and Data Mining: Challenges and Realities with Real World Data. Zhu, Q, and Davidson, I., editors. Idea Group Publishing, Hershey, PA
    • (2006) Knowledge Discovery and Data Mining: Challenges and Realities with Real World Data
    • Bruckhaus, T.1
  • 12
    • 0003641269 scopus 로고    scopus 로고
    • Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., and Uthurusamy, R. (editors), AAAI/MIT Press
    • Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., and Uthurusamy, R. (editors). 1996. Advances in Knowledge Discovery and Data Mining, AAAI/MIT Press.
    • (1996) Advances in Knowledge Discovery and Data Mining
  • 18
    • 0036565589 scopus 로고    scopus 로고
    • An instance-weighting method to induce cost-sensitive trees
    • Ting, K.M. 2002. An Instance-Weighting Method to Induce Cost-Sensitive Trees. IEEE Transactions on Knowledge and Data Engineering, 14(3):659-665.
    • (2002) IEEE Transactions on Knowledge and Data Engineering , vol.14 , Issue.3 , pp. 659-665
    • Ting, K.M.1
  • 19
    • 0000865580 scopus 로고
    • Cost-sensitive classification: Empirical evaluation of a hybrid genetic decision tree induction algorithm
    • Turney, P.D. 1995. Cost-Sensitive Classification: Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm. Journal of Artificial Intelligence Research 2:369409.
    • (1995) Journal of Artificial Intelligence Research , vol.2 , pp. 369409
    • Turney, P.D.1
  • 20
    • 1442275185 scopus 로고    scopus 로고
    • Learning when training data are costly: The effect of class distribution on tree induction
    • Weiss, G., and Provost, F. 2003. Learning when Training Data are Costly: The Effect of Class Distribution on Tree Induction. Journal of Artificial Intelligence Research 19: 315-354.
    • (2003) Journal of Artificial Intelligence Research , vol.19 , pp. 315-354
    • Weiss, G.1    Provost, F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.