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Volumn 125, Issue , 2008, Pages 205-230

A comparative study of several genetic-based supervised learning systems

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EID: 46949084846     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-78979-6_10     Document Type: Article
Times cited : (6)

References (53)
  • 6
    • 0043284115 scopus 로고    scopus 로고
    • Accuracy-Based Learning Classifier Systems: Models, Analysis and Applications to Classification Tasks
    • E. Bernadó-Mansilla and J.M. Garrell. Accuracy-Based Learning Classifier Systems: Models, Analysis and Applications to Classification Tasks. Evolutionary Computation, 11(3):209-238, 2003.
    • (2003) Evolutionary Computation , vol.11 , Issue.3 , pp. 209-238
    • Bernadó-Mansilla, E.1    Garrell, J.M.2
  • 7
    • 84949196940 scopus 로고    scopus 로고
    • XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining
    • Advances in Learning Classifier Systems, of, Springer, Berlin Heidelberg New York
    • E. Bernadó-Mansilla, X. Llorà, and J.M. Garrell. XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining. In Advances in Learning Classifier Systems, volume 2321 of LNAI pages 115-132. Springer, Berlin Heidelberg New York, 2002.
    • (2002) LNAI , vol.2321 , pp. 115-132
    • Bernadó-Mansilla, E.1    Llorà, X.2    Garrell, J.M.3
  • 9
    • 0002743228 scopus 로고
    • An efficient classifier system and its experimental comparison with two representative learning methods on three medical domains
    • P. Bonelli and A. Parodi. An efficient classifier system and its experimental comparison with two representative learning methods on three medical domains. In 4th International Conference on Genetic Algorithms, pages 288-295, 1991.
    • (1991) 4th International Conference on Genetic Algorithms , pp. 288-295
    • Bonelli, P.1    Parodi, A.2
  • 10
    • 0035897955 scopus 로고    scopus 로고
    • Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm
    • L. Castillo, A. González, and R. Pérez. Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm. Fuzzy Sets and Systems, 120:309-321, 2001.
    • (2001) Fuzzy Sets and Systems , vol.120 , pp. 309-321
    • Castillo, L.1    González, A.2    Pérez, R.3
  • 15
    • 29644438050 scopus 로고    scopus 로고
    • Statistical Comparisons of Classifiers over Multiple Data Sets
    • J. Dems̃ar. Statistical Comparisons of Classifiers over Multiple Data Sets. Journal of Machine Learning Research, 7:1-30, 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1-30
    • Dems̃ar, J.1
  • 22
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • J. Friedman, T. Hastie, and R. Tibshirani. Additive logistic regression: a statistical view of boosting. Annals of Statistics, 32(2):337-374, 2000.
    • (2000) Annals of Statistics , vol.32 , Issue.2 , pp. 337-374
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 23
    • 84944811700 scopus 로고
    • The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance
    • M. Friedman. The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance. Journal of the American Statistical Association, 32:675-701, 1937.
    • (1937) Journal of the American Statistical Association , vol.32 , pp. 675-701
    • Friedman, M.1
  • 24
    • 0001837148 scopus 로고
    • A Comparison of Alternative Tests of Significance for the Problem of m Rankings
    • M. Friedman. A Comparison of Alternative Tests of Significance for the Problem of m Rankings. Annals of Mathematical Statistics, 11:86-92, 1940.
    • (1940) Annals of Mathematical Statistics , vol.11 , pp. 86-92
    • Friedman, M.1
  • 28
    • 0032069167 scopus 로고    scopus 로고
    • Completeness and Consistency Conditions for Learning Fuzzy Rules
    • A. Gónzalez and R. Pérez. Completeness and Consistency Conditions for Learning Fuzzy Rules. Fuzzy Sets and Systems, 96:37-51, 1998.
    • (1998) Fuzzy Sets and Systems , vol.96 , pp. 37-51
    • Gónzalez, A.1    Pérez, R.2
  • 29
    • 0033116171 scopus 로고    scopus 로고
    • SLAVE: A Genetic Learning System Based on an Iterative Approach
    • A. Gónzalez and R. Pérez. SLAVE: A Genetic Learning System Based on an Iterative Approach. IEEE Transactions on Fuzzy Systems, 7(2):176-191, 1999.
    • (1999) IEEE Transactions on Fuzzy Systems , vol.7 , Issue.2 , pp. 176-191
    • Gónzalez, A.1    Pérez, R.2
  • 31
    • 0000746883 scopus 로고
    • Escaping Brittleness: The possibilities of General-Purpose Learning Algorithms Applied to Parallel Rule-Based Systems
    • Michalski Mitchell and Carbonell, editors, Machine Learning, an artificial intelligence approach, of, Morgan Kaufmann, San Francisco
    • J.H Holland. Escaping Brittleness: The possibilities of General-Purpose Learning Algorithms Applied to Parallel Rule-Based Systems. In Michalski Mitchell and Carbonell, editors, Machine Learning, an artificial intelligence approach, volume II of Lecture Notes in Artificial Intelligence, pages 593-623. Morgan Kaufmann, San Francisco, 1986.
    • (1986) Lecture Notes in Artificial Intelligence , vol.2 , pp. 593-623
    • Holland, J.H.1
  • 32
    • 0027696178 scopus 로고
    • A Knowledge-Intensive Genetic Algorithm for Supervised Learning
    • C.Z. Janikow. A Knowledge-Intensive Genetic Algorithm for Supervised Learning. Machine Learning, 13(2-3):189-228, 1993.
    • (1993) Machine Learning , vol.13 , Issue.2-3 , pp. 189-228
    • Janikow, C.Z.1
  • 33
    • 0000468432 scopus 로고
    • Estimating Continuous Distributions in Bayesian Classifiers
    • Morgan Kaufmann, San Francisco
    • G.H. John and P. Langley. Estimating Continuous Distributions in Bayesian Classifiers. In 11th Conference on Uncertainty in Artificial Intelligence, pages 338-345. Morgan Kaufmann, San Francisco, 1995.
    • (1995) 11th Conference on Uncertainty in Artificial Intelligence , pp. 338-345
    • John, G.H.1    Langley, P.2
  • 34
    • 4444378339 scopus 로고    scopus 로고
    • Evolving neural network using real coded genetic algorithm (GA) for multispectral image classification
    • Z. Liu, A. Liu, C. Wang, and Z. Niu. Evolving neural network using real coded genetic algorithm (GA) for multispectral image classification. Future Generation Computer Systems, 20(7):1119-1129, 2004.
    • (2004) Future Generation Computer Systems , vol.20 , Issue.7 , pp. 1119-1129
    • Liu, Z.1    Liu, A.2    Wang, C.3    Niu, Z.4
  • 36
    • 33646036159 scopus 로고    scopus 로고
    • Induction of descriptive fuzzy classifiers with the logitboost algorithm
    • J. Otero and L. Sánchez. Induction of descriptive fuzzy classifiers with the logitboost algorithm. Soft Computing, 10(9):825-835, 2006.
    • (2006) Soft Computing , vol.10 , Issue.9 , pp. 825-835
    • Otero, J.1    Sánchez, L.2
  • 37
    • 41749115020 scopus 로고    scopus 로고
    • Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms
    • of, Springer, Berlin Heidelberg New York
    • M. Pelikan. Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms, volume 170 of Studies in Computational Intelligence. Springer, Berlin Heidelberg New York, 2005.
    • (2005) Studies in Computational Intelligence , vol.170
    • Pelikan, M.1
  • 38
    • 34147154444 scopus 로고    scopus 로고
    • Scalable Optimization via Probabilistic Modeling
    • of, Springer, Berlin Heidelberg New York
    • M. Pelikan, K. Sastry, and E. Cantú-Paz. Scalable Optimization via Probabilistic Modeling, volume 33 of Studies in Computational Intelligence. Springer, Berlin Heidelberg New York, 2006.
    • (2006) Studies in Computational Intelligence , vol.33
    • Pelikan, M.1    Sastry, K.2    Cantú-Paz, E.3
  • 39
    • 0003120218 scopus 로고    scopus 로고
    • Fast Training of Support Vector Machines using Sequential Minimal Opt
    • MIT Press
    • J. Platt. Fast Training of Support Vector Machines using Sequential Minimal Opt. In Advances in Kernel Methods - Support Vector Lear. MIT Press, 1998.
    • (1998) Advances in Kernel Methods - Support Vector Lear
    • Platt, J.1
  • 41
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • J. Rissanen. Modeling by shortest data description. Automatica, vol. 14:465-471, 1978.
    • (1978) Automatica , vol.14 , pp. 465-471
    • Rissanen, J.1
  • 42
    • 0033281701 scopus 로고    scopus 로고
    • Improved Boosting Algorithms using Confidence-Rated Predictions
    • R.E. Schapire and Y. Singer. Improved Boosting Algorithms using Confidence-Rated Predictions. Machine Learning, 37(3):297-336, 1999.
    • (1999) Machine Learning , vol.37 , Issue.3 , pp. 297-336
    • Schapire, R.E.1    Singer, Y.2
  • 45
    • 0000259511 scopus 로고    scopus 로고
    • Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
    • T.G. Dietterich. Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms. Neural Computation, 10(7):1895-1924, 1998.
    • (1998) Neural Computation , vol.10 , Issue.7 , pp. 1895-1924
    • Dietterich, T.G.1
  • 47
    • 84971641220 scopus 로고
    • SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes Based Concepts
    • P. B. Brazdil, editor, Springer, Berlin Heidelberg New York
    • G. Venturini. SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes Based Concepts. In P. B. Brazdil, editor, Machine Learning: ECML-93 - Proceedings of the European Conference on Machine Learning, pages 280-296. Springer, Berlin Heidelberg New York, 1993.
    • (1993) Machine Learning: ECML-93 - Proceedings of the European Conference on Machine Learning , pp. 280-296
    • Venturini, G.1
  • 49
    • 0001884644 scopus 로고
    • Individual Comparisons by RankingMethods
    • F. Wilcoxon. Individual Comparisons by RankingMethods. Biometrics, 1:80-83, 1945.
    • (1945) Biometrics , vol.1 , pp. 80-83
    • Wilcoxon, F.1
  • 50
    • 0001387704 scopus 로고
    • Classifier Fitness Based on Accuracy
    • S.W. Wilson. Classifier Fitness Based on Accuracy. Evolutionary Computation, 3(2):149-175, 1995.
    • (1995) Evolutionary Computation , vol.3 , Issue.2 , pp. 149-175
    • Wilson, S.W.1
  • 51
    • 0000648788 scopus 로고    scopus 로고
    • Generalization in the XCS Classifier System
    • Morgan Kaufmann, San Francisco
    • S.W. Wilson. Generalization in the XCS Classifier System. In 3rd Annual Conference on Genetic Programming, pages 665-674. Morgan Kaufmann, San Francisco, 1998.
    • (1998) 3rd Annual Conference on Genetic Programming , pp. 665-674
    • Wilson, S.W.1
  • 52
    • 84949235142 scopus 로고    scopus 로고
    • Compact Rulesets from XCSI
    • Advances in Learning Classifier Systems, 4th International Workshop, of, Springer, Berlin Heidelberg New York
    • S.W. Wilson. Compact Rulesets from XCSI. In Advances in Learning Classifier Systems, 4th International Workshop, volume 2321 of Lecture Notes in Artificial Intelligence, pages 197-210. Springer, Berlin Heidelberg New York, 2002.
    • (2002) Lecture Notes in Artificial Intelligence , vol.2321 , pp. 197-210
    • Wilson, S.W.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.