메뉴 건너뛰기




Volumn 36, Issue 3 PART 1, 2009, Pages 4517-4522

Fuzzy classification systems based on fuzzy information gain measures

Author keywords

Classification problems; Feature weights; Fuzzy entropy; Fuzzy information gain; Membership grades

Indexed keywords

ARTIFICIAL INTELLIGENCE; ENTROPY; LEARNING SYSTEMS; MEMBERSHIP FUNCTIONS; SET THEORY;

EID: 58349110117     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.05.020     Document Type: Article
Times cited : (16)

References (31)
  • 2
    • 34250698677 scopus 로고
    • A language for the description of concepts
    • Banerji R.B. A language for the description of concepts. General Systems 9 1 (1964) 135-141
    • (1964) General Systems , vol.9 , Issue.1 , pp. 135-141
    • Banerji, R.B.1
  • 3
    • 0026966646 scopus 로고    scopus 로고
    • Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992). A training algorithm for optimal margin classifiers. In Proceedings of the fifth annual workshop on computational learning theory, Pittsburgh, Pennsylvania (pp. 144-152).
    • Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992). A training algorithm for optimal margin classifiers. In Proceedings of the fifth annual workshop on computational learning theory, Pittsburgh, Pennsylvania (pp. 144-152).
  • 4
    • 58349100245 scopus 로고    scopus 로고
    • Caruana, R., & Freitag, D. (1994). Greedy attribute selection. In Proceedings of international conference on machine learning, New Brunswick, New Jersey (pp. 28-36).
    • Caruana, R., & Freitag, D. (1994). Greedy attribute selection. In Proceedings of international conference on machine learning, New Brunswick, New Jersey (pp. 28-36).
  • 5
    • 37749034335 scopus 로고    scopus 로고
    • Catlett, J. (1991). On changing continuous attributes into ordered discretize attributes. In Proceedings of the fifth european working session on learning, Berlin, Germany (pp. 164-178).
    • Catlett, J. (1991). On changing continuous attributes into ordered discretize attributes. In Proceedings of the fifth european working session on learning, Berlin, Germany (pp. 164-178).
  • 6
    • 0033307788 scopus 로고    scopus 로고
    • Chaikla, N., & Qi, Y. (1999). Genetic algorithms in feature selection. In Proceedings of the 1999 IEEE international conference on systems, man, and cybernetics, Tokyo, Japan (Vol. 5, pp. 538-540).
    • Chaikla, N., & Qi, Y. (1999). Genetic algorithms in feature selection. In Proceedings of the 1999 IEEE international conference on systems, man, and cybernetics, Tokyo, Japan (Vol. 5, pp. 538-540).
  • 7
    • 23944443563 scopus 로고    scopus 로고
    • Chen, S. M., & Shie, J. D. (2005). A new method for feature subset selection for handling classification problems. In Proceedings of the 2005 IEEE international conference on fuzzy systems, Reno, Nevada (pp. 183-188).
    • Chen, S. M., & Shie, J. D. (2005). A new method for feature subset selection for handling classification problems. In Proceedings of the 2005 IEEE international conference on fuzzy systems, Reno, Nevada (pp. 183-188).
  • 8
    • 19544383423 scopus 로고    scopus 로고
    • A new method to construct membership functions and generate weighted fuzzy rules from training instances
    • Chen S.M., and Chang C.H. A new method to construct membership functions and generate weighted fuzzy rules from training instances. Cybernetics and Systems 36 4 (2005) 397-414
    • (2005) Cybernetics and Systems , vol.36 , Issue.4 , pp. 397-414
    • Chen, S.M.1    Chang, C.H.2
  • 9
    • 0036924127 scopus 로고    scopus 로고
    • Automatically constructing membership functions and generating fuzzy rules using genetic algorithms
    • Chen S.M., and Chen Y.C. Automatically constructing membership functions and generating fuzzy rules using genetic algorithms. Cybernetics and Systems 33 8 (2002) 841-862
    • (2002) Cybernetics and Systems , vol.33 , Issue.8 , pp. 841-862
    • Chen, S.M.1    Chen, Y.C.2
  • 10
    • 0036795586 scopus 로고    scopus 로고
    • Generating fuzzy rules from training data containing noise for handling classification problems
    • Chen S.M., Kao C.H., and Yu C.H. Generating fuzzy rules from training data containing noise for handling classification problems. Cybernetics and Systems 33 7 (2002) 723-748
    • (2002) Cybernetics and Systems , vol.33 , Issue.7 , pp. 723-748
    • Chen, S.M.1    Kao, C.H.2    Yu, C.H.3
  • 11
    • 58349110915 scopus 로고    scopus 로고
    • Chmielewski, M. R., & Grzymala-Busse, J. W. (1994). Global discretization of continuous attributes as preprocessing for machine learning. In Proceedings of the third international workshop on rough sets and soft computing, San Jose, California (pp. 294-301).
    • Chmielewski, M. R., & Grzymala-Busse, J. W. (1994). Global discretization of continuous attributes as preprocessing for machine learning. In Proceedings of the third international workshop on rough sets and soft computing, San Jose, California (pp. 294-301).
  • 13
    • 0031245693 scopus 로고    scopus 로고
    • Feature analysis: Neural network and fuzzy set theoretic approaches
    • De R.K., Pal N.R., and Pal S.K. Feature analysis: Neural network and fuzzy set theoretic approaches. Pattern Recognition 30 10 (1997) 1579-1590
    • (1997) Pattern Recognition , vol.30 , Issue.10 , pp. 1579-1590
    • De, R.K.1    Pal, N.R.2    Pal, S.K.3
  • 14
    • 58349101284 scopus 로고    scopus 로고
    • Fayyad, U., & Irani, K. (1993). Multi-interval discretization of continuous-valued attributes for classification learning. In Proceedings of the 13th international joint conference on artificial intelligence, Chambery, France (pp. 1022-1027).
    • Fayyad, U., & Irani, K. (1993). Multi-interval discretization of continuous-valued attributes for classification learning. In Proceedings of the 13th international joint conference on artificial intelligence, Chambery, France (pp. 1022-1027).
  • 15
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • Fisher R.A. The use of multiple measurements in taxonomic problems. Annals of Eugenics 7 2 (1936) 179-188
    • (1936) Annals of Eugenics , vol.7 , Issue.2 , pp. 179-188
    • Fisher, R.A.1
  • 16
    • 27144559417 scopus 로고    scopus 로고
    • Gomez, J., Garcia, A., & Silva, C. (2005). COFRE: A fuzzy rule coevolutionary approach for multiclass classification problems. In Proceedings of the 2005 IEEE congress on evolutionary computation, Edinburgh, UK (pp. 1637-1644).
    • Gomez, J., Garcia, A., & Silva, C. (2005). COFRE: A fuzzy rule coevolutionary approach for multiclass classification problems. In Proceedings of the 2005 IEEE congress on evolutionary computation, Edinburgh, UK (pp. 1637-1644).
  • 18
    • 11944266539 scopus 로고
    • Information theory and statistical mechanics
    • Jaynes E.T. Information theory and statistical mechanics. Physical Review 106 4 (1957) 620-630
    • (1957) Physical Review , vol.106 , Issue.4 , pp. 620-630
    • Jaynes, E.T.1
  • 19
    • 58349088487 scopus 로고    scopus 로고
    • John, G. H., & Langley, P. (1995). Estimating continuous distributions in Bayesian classifiers. In Proceedings of the 11th conference on uncertainty in artificial intelligence, Montreal, Canada (pp. 338-345).
    • John, G. H., & Langley, P. (1995). Estimating continuous distributions in Bayesian classifiers. In Proceedings of the 11th conference on uncertainty in artificial intelligence, Montreal, Canada (pp. 338-345).
  • 20
    • 84958088127 scopus 로고    scopus 로고
    • Maas, W. (1994). Efficient agnostic PAC-learning with simple hypotheses. In Proceedings of the seventh annual ACM conference on computational learning theory, New Brunswick, New Jersey (pp. 67-75).
    • Maas, W. (1994). Efficient agnostic PAC-learning with simple hypotheses. In Proceedings of the seventh annual ACM conference on computational learning theory, New Brunswick, New Jersey (pp. 67-75).
  • 21
    • 51249194645 scopus 로고
    • A logical calculus of the ideas immanent in nervous activity
    • McCulloch W.S., and Pitts W. A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics 5 1 (1943) 115-133
    • (1943) Bulletin of Mathematical Biophysics , vol.5 , Issue.1 , pp. 115-133
    • McCulloch, W.S.1    Pitts, W.2
  • 22
    • 7744239513 scopus 로고    scopus 로고
    • Ongkowijaya, B. T., & Xiaoyan, Z. (2004). A new weighted feature approach based on GA for speech recognition. In Proceedings of the 7th international conference on signal processing, Istanbul, Turkey (pp. 663-666).
    • Ongkowijaya, B. T., & Xiaoyan, Z. (2004). A new weighted feature approach based on GA for speech recognition. In Proceedings of the 7th international conference on signal processing, Istanbul, Turkey (pp. 663-666).
  • 23
    • 84898983292 scopus 로고    scopus 로고
    • Platt, J. C. (1999). Using analytic QP and sparseness to speed training of support vector machines. In Proceedings of the 13th annual conference on neural information processing systems, Denver, Colorado (pp. 557-563).
    • Platt, J. C. (1999). Using analytic QP and sparseness to speed training of support vector machines. In Proceedings of the 13th annual conference on neural information processing systems, Denver, Colorado (pp. 557-563).
  • 24
    • 33744584654 scopus 로고
    • Induction of decision trees
    • Quinlan J.R. Induction of decision trees. Machine Learning 1 1 (1986) 81-106
    • (1986) Machine Learning , vol.1 , Issue.1 , pp. 81-106
    • Quinlan, J.R.1
  • 26
    • 0033079110 scopus 로고    scopus 로고
    • Off-line signature verification using genetically optimized weighted features
    • Ramesh V.E., and Murty M.N. Off-line signature verification using genetically optimized weighted features. Pattern Recognition 32 1 (1999) 217-233
    • (1999) Pattern Recognition , vol.32 , Issue.1 , pp. 217-233
    • Ramesh, V.E.1    Murty, M.N.2
  • 27
    • 58349110299 scopus 로고    scopus 로고
    • Shie, J. D., & Chen, S. M. (2006). A new approach for handling classification problems based on fuzzy information gain measures. In Proceedings of the 2006 IEEE international conference on fuzzy systems, Vancouver, BC, Canada (pp. 5427-5434).
    • Shie, J. D., & Chen, S. M. (2006). A new approach for handling classification problems based on fuzzy information gain measures. In Proceedings of the 2006 IEEE international conference on fuzzy systems, Vancouver, BC, Canada (pp. 5427-5434).
  • 28
    • 37649019425 scopus 로고    scopus 로고
    • Feature subset selection based on fuzzy entropy measures for handling classification problems
    • Shie J.D., and Chen S.M. Feature subset selection based on fuzzy entropy measures for handling classification problems. Applied Intelligence 28 1 (2007) 69-82
    • (2007) Applied Intelligence , vol.28 , Issue.1 , pp. 69-82
    • Shie, J.D.1    Chen, S.M.2
  • 29
    • 33847169571 scopus 로고    scopus 로고
    • Winkler, S. M., Affenzeller, M., & Wagner, S. (2006). Advances in applying genetic programming to machine learning, focusing on classification problems. In Proceedings of the 20th international symposium on parallel and distributed processing, Rhodes Island, Greece (pp. 2295-2302).
    • Winkler, S. M., Affenzeller, M., & Wagner, S. (2006). Advances in applying genetic programming to machine learning, focusing on classification problems. In Proceedings of the 20th international symposium on parallel and distributed processing, Rhodes Island, Greece (pp. 2295-2302).
  • 31
    • 0016458950 scopus 로고
    • The concept of linguistic variable and its application to approximate reasoning - I
    • Zadeh L.A. The concept of linguistic variable and its application to approximate reasoning - I. Information Sciences 8 3 (1975) 199-245
    • (1975) Information Sciences , vol.8 , Issue.3 , pp. 199-245
    • Zadeh, L.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.