메뉴 건너뛰기




Volumn 17, Issue 3, 1999, Pages 223-232

Association, statistical, mathematical and neural approaches for mining breast cancer patterns

Author keywords

Artificial neural networks; Data envelopment analysis; Data mining

Indexed keywords


EID: 0000532568     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0957-4174(99)00036-6     Document Type: Article
Times cited : (95)

References (45)
  • 6
    • 0032172083 scopus 로고    scopus 로고
    • Inductive, evolutionary and neural techniques for discrimination: A comparative study
    • Bhattacharyya, S., & Pendharkar, P. C. (1998). Inductive, evolutionary and neural techniques for discrimination: a comparative study. Decision Sciences, 28 (4), 000.
    • (1998) Decision Sciences , vol.28 , Issue.4
    • Bhattacharyya, S.1    Pendharkar, P.C.2
  • 8
    • 0002607026 scopus 로고    scopus 로고
    • Bayesian classification (AutoClass): Theory and results
    • U. M. Fayyad & G. Piatetsky-Shapiro & R. Uthurusamy (Eds.), Cambridge, MA: AAAI/MIT Press
    • Cheeseman, P., & Stutz, J. (1996). Bayesian classification (AutoClass): theory and results. In U. M. Fayyad & G. Piatetsky-Shapiro & R. Uthurusamy (Eds.), Advances in knowledge discovery and data mining, (pp. 153-180). Cambridge, MA: AAAI/MIT Press.
    • (1996) Advances in Knowledge Discovery and Data Mining , pp. 153-180
    • Cheeseman, P.1    Stutz, J.2
  • 13
    • 84985757179 scopus 로고
    • Rule-based expert systems and linear models: An empirical comparison of learning-by-examples methods
    • Chung, H. M., & Silver, M. S. (1992). Rule-based expert systems and linear models: an empirical comparison of learning-by-examples methods. Decision Sciences, 23, 687-707.
    • (1992) Decision Sciences , vol.23 , pp. 687-707
    • Chung, H.M.1    Silver, M.S.2
  • 14
    • 0012017520 scopus 로고
    • Progress in machine learning (from the Proceedings of the Second European Working Session on Learning)
    • Yugoslavia: Sigma Press
    • Clark, P., & Niblett, T. (1987). Progress in machine learning (from the Proceedings of the Second European Working Session on Learning), (pp. 11 -30). Induction in noisy domains Bled, Yugoslavia: Sigma Press.
    • (1987) Induction in Noisy Domains Bled , pp. 11-30
    • Clark, P.1    Niblett, T.2
  • 15
    • 34249966007 scopus 로고
    • The CN2 induction algorithm
    • Clark, P., & Niblett, T. (1987). The CN2 induction algorithm. Machine Learning, 3 (4), 261-283.
    • (1987) Machine Learning , vol.3 , Issue.4 , pp. 261-283
    • Clark, P.1    Niblett, T.2
  • 17
    • 84957712272 scopus 로고
    • Knowledge discovery in large spatial databases: Focusing techniques for efficient class identification
    • Portland, Maine
    • Ester, M., Kriegel, H.P., Xu, X. (1995). Knowledge discovery in large spatial databases: focusing techniques for efficient class identification. Proceedings Fourth International Symposium of Large Spatial Databases (pp. 67-82). Portland, Maine.
    • (1995) Proceedings Fourth International Symposium of Large Spatial Databases , pp. 67-82
    • Ester, M.1    Kriegel, H.P.2    Xu, X.3
  • 18
    • 84976803260 scopus 로고
    • FastMap: A fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets
    • Faloutsos, C., & Lin, K. I. (1995). FastMap: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets. Proceedings ACM Sigmoid, 163-174.
    • (1995) Proceedings ACM Sigmoid , pp. 163-174
    • Faloutsos, C.1    Lin, K.I.2
  • 20
    • 84989432337 scopus 로고
    • A linear programming approach to the discriminant problem
    • Freed, N., & Glover, F. (1981). A linear programming approach to the discriminant problem. Decision Sciences, 12, 68-74.
    • (1981) Decision Sciences , vol.12 , pp. 68-74
    • Freed, N.1    Glover, F.2
  • 21
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, 179-188.
    • (1936) Annals of Eugenics , vol.7 , pp. 179-188
    • Fisher, R.A.1
  • 23
    • 0003218928 scopus 로고
    • Improving inference through conceptual clustering
    • Seattle
    • Fisher, D. (1987). Improving inference through conceptual clustering. Proceedings AAAI Conference (pp. 461-465). Seattle.
    • (1987) Proceedings AAAI Conference , pp. 461-465
    • Fisher, D.1
  • 28
    • 0026225194 scopus 로고
    • Linear discriminant functions determined through genetic search
    • Koehler, G. J. (1991). Linear discriminant functions determined through genetic search. ORSA Journal on Computing, 3 (4), 345-357.
    • (1991) ORSA Journal on Computing , vol.3 , Issue.4 , pp. 345-357
    • Koehler, G.J.1
  • 32
    • 85005299854 scopus 로고
    • The multi-purpose incremental learning system aq15 and its testing application to three medical domains
    • Philadelphia, PA: Morgan Kauffman
    • Michalski, R.S., Mozetic, I., Hong, J., Lavrac, N. (1986). The multi-purpose incremental learning system aq15 and its testing application to three medical domains. Proceedings of the Fifth National Conference on Artificial Intelligence (pp. 1041-1045). Philadelphia, PA: Morgan Kauffman.
    • (1986) Proceedings of the Fifth National Conference on Artificial Intelligence , pp. 1041-1045
    • Michalski, R.S.1    Mozetic, I.2    Hong, J.3    Lavrac, N.4
  • 34
    • 84976830511 scopus 로고
    • Efficient parallel data mining for association rules
    • Park, J. S., Chen, M. S., & Yu, P. S. (1995). Efficient parallel data mining for association rules. Proceedings ACM SIGMOD, 175-186.
    • (1995) Proceedings ACM SIGMOD , pp. 175-186
    • Park, J.S.1    Chen, M.S.2    Yu, P.S.3
  • 35
    • 0011687525 scopus 로고    scopus 로고
    • Discovering value in a mountain of data
    • Pass, S. (1997). Discovering value in a mountain of data. OR/MS Today, 24-28.
    • (1997) OR/MS Today , pp. 24-28
    • Pass, S.1
  • 37
    • 33744584654 scopus 로고
    • Induction of Decision Trees
    • Quinlan, J. R. (1986). Induction of Decision Trees. Machine Learning, 1, 81-106.
    • (1986) Machine Learning , vol.1 , pp. 81-106
    • Quinlan, J.R.1
  • 40
    • 0026119038 scopus 로고
    • Symbolic and neural learning algorithms: An experimental comparison
    • Shavlik, J. W., Mooney, R. J., & Towell, G. G. (1991). Symbolic and neural learning algorithms: an experimental comparison. Machine Learning, 6, 111-143.
    • (1991) Machine Learning , vol.6 , pp. 111-143
    • Shavlik, J.W.1    Mooney, R.J.2    Towell, G.G.3
  • 42
    • 0037894881 scopus 로고
    • The potential use of DEA for credit applicant acceptance systems
    • Troutt, M. D., Rai, A., & Zhang, A. (1995). The potential use of DEA for credit applicant acceptance systems. Computers and Operations Research, 4, 405-408.
    • (1995) Computers and Operations Research , vol.4 , pp. 405-408
    • Troutt, M.D.1    Rai, A.2    Zhang, A.3
  • 43
    • 0001512820 scopus 로고
    • An empirical comparison of pattern recognition, neural nets, and machine learning classification methods
    • Detroit, MI. Los Altos, CA: Morgan Kaufmann
    • Weiss, S.M., Kapouleas, I. (1989). An empirical comparison of pattern recognition, neural nets, and machine learning classification methods. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (pp. 688-693). Detroit, MI. Los Altos, CA: Morgan Kaufmann.
    • (1989) Proceedings of the Eleventh International Joint Conference on Artificial Intelligence , pp. 688-693
    • Weiss, S.M.1    Kapouleas, I.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.