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Volumn 17, Issue 2-3, 2011, Pages 255-287

KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework

Author keywords

Data mining; Data set repository; Evolutionary algorithms; Java; Knowledge extraction; Machine learning

Indexed keywords

DATA MANAGEMENT; DATA MINING PROBLEMS; DATA SET REPOSITORY; DATA SETS; DATA-MINING SOFTWARE; EVOLUTIONARY LEARNING; EXPERIMENTAL ANALYSIS; JAVA; KNOWLEDGE EXTRACTION; MACHINE LEARNING; OPEN SOURCE SOFTWARE; PATTERN MINING;

EID: 79951829331     PISSN: 15423980     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (2263)

References (48)
  • 6
    • 27144531570 scopus 로고    scopus 로고
    • A study of the behaviour of several methods for balancing machine learning training data
    • Gustavo E. A. P. A. Batista, Ronaldo C. Prati, and María Carolina Monard. (2004). A study of the behaviour of several methods for balancing machine learning training data. SIGKDD Explorations, 6(1):20-29.
    • (2004) SIGKDD Explorations , vol.6 , Issue.1 , pp. 20-29
    • Batista, G.E.A.P.A.1    Prati, R.C.2    Monard, M.C.3
  • 7
    • 0009038905 scopus 로고
    • Improvements of general multiple test procedures for redundant systems of hypotheses
    • In G. Hommel P. Bauer and E. Sonnemann, editors, Springer, Berlin
    • G. Bergmann and G. Hommel. (1988). Improvements of general multiple test procedures for redundant systems of hypotheses. In G. Hommel P. Bauer and E. Sonnemann, editors, Multiple Hypotheses Testing, page 100-115. Springer, Berlin.
    • (1988) Multiple Hypotheses Testing , pp. 100-115
    • Bergmann, G.1    Hommel, G.2
  • 8
    • 15744374385 scopus 로고    scopus 로고
    • Genetic fuzzy systems: Evolutionary tuning and learning of fuzzy knowledge bases
    • O. Cordón, F. Herrera, F. Hoffmann, and L. Magdalena. (2001). Genetic fuzzy systems: Evolutionary tuning and learning of fuzzy knowledge bases. World Scientific.
    • (2001) World Scientific
    • Cordón, O.1    Herrera, F.2    Hoffmann, F.3    Magdalena, L.4
  • 10
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • J. Demšar. (2006). Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7:1-30. (Pubitemid 43022939)
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1-30
    • Demsar, J.1
  • 11
    • 0000259511 scopus 로고    scopus 로고
    • Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
    • T.G. Dietterich. (1998). Approximate statistical tests for comparing supervised classification learning algorithms. Neural Computation, 10(7):1895-1923. (Pubitemid 128463689)
    • (1998) Neural Computation , vol.10 , Issue.7 , pp. 1895-1923
    • Dietterich, T.G.1
  • 12
    • 0030649484 scopus 로고    scopus 로고
    • Solving the multiple instance problem with axis-parallel rectangles
    • PII S0004370296000343
    • T.G. Dietterich, R.H. Lathrop, and T. Lozano-Perez. (1997). Solving the multiple instance problem with axis-parallel rectangles. Artifical Intelligence, 89(1-2):31-71. (Pubitemid 127412230)
    • (1997) Artificial Intelligence , vol.89 , Issue.1-2 , pp. 31-71
    • Dietterich, T.G.1    Lathrop, R.H.2    Lozano-Perez, T.3
  • 17
    • 84944811700 scopus 로고
    • The use of ranks to avoid the assumption of normality implicit in the analysis of variance
    • M. Friedman. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association, 32(200):675-701.
    • (1937) Journal of the American Statistical Association , vol.32 , Issue.200 , pp. 675-701
    • Friedman, M.1
  • 18
    • 64549120231 scopus 로고    scopus 로고
    • A study of statistical techniques and performance measures for genetics-based machine learning: Accuracy and interpretability
    • S. García, A. Fernández, J. Luengo, and F. Herrera. (2009). A study of statistical techniques and performance measures for genetics-based machine learning: Accuracy and interpretability. Soft Computing, 13(10):959-977.
    • (2009) Soft Computing , vol.13 , Issue.10 , pp. 959-977
    • García, S.1    Fernández, A.2    Luengo, J.3    Herrera, F.4
  • 19
    • 77549084648 scopus 로고    scopus 로고
    • Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
    • DOI: 10.1016/j.ins.2009.12.010
    • S. García, A. Fernández, J. Luengo, and F. Herrera. (2010). Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power. Information Sciences. DOI: 10.1016/j.ins.2009.12.010.
    • (2010) Information Sciences
    • García, S.1    Fernández, A.2    Luengo, J.3    Herrera, F.4
  • 20
    • 58149287952 scopus 로고    scopus 로고
    • An extension on statistical comparisons of classifiers over multiple data sets for all pairwise comparisons
    • S. García and F. Herrera. (2008). An extension on statistical comparisons of classifiers over multiple data sets for all pairwise comparisons. Journal of Machine Learning Research, 9:2579-2596.
    • (2008) Journal of Machine Learning Research , vol.9 , pp. 2579-2596
    • García, S.1    Herrera, F.2
  • 21
    • 70349270458 scopus 로고    scopus 로고
    • A study on the use of nonparametric tests for analyzing the evolutionary algorithms' behaviour: A case study on the cec'2005 special session on real parameter optimization
    • S. García, D. Molina, M. Lozano, and F. Herrera. (2009). A study on the use of nonparametric tests for analyzing the evolutionary algorithms' behaviour: A case study on the cec'2005 special session on real parameter optimization. Journal of Heuristics, 15: 617-644.
    • (2009) Journal of Heuristics , vol.15 , pp. 617-644
    • García, S.1    Molina, D.2    Lozano, M.3    Herrera, F.4
  • 23
    • 35548967562 scopus 로고    scopus 로고
    • Classification tree analysis using TARGET
    • DOI 10.1016/j.csda.2007.03.014, PII S016794730700117X
    • J. Brian Gray and Guangzhe Fan. (2008). Classification tree analysis using TARGET. Computational Statistics & Data Analysis, 52(3):1362-1372. (Pubitemid 350007780)
    • (2008) Computational Statistics and Data Analysis , vol.52 , Issue.3 , pp. 1362-1372
    • Gray, J.B.1    Fan, G.2
  • 26
    • 0003585297 scopus 로고    scopus 로고
    • Morgan Kaufmann Publishers Inc, San Francisco, CA, USA, 2nd edition
    • J. Han and M. Kamber. (2006). Data mining: Concepts and Techniques. Morgan Kaufmann Publishers Inc, San Francisco, CA, USA, 2nd edition.
    • (2006) Data Mining: Concepts and Techniques
    • Han, J.1    Kamber, M.2
  • 27
    • 0002322469 scopus 로고
    • On a test of whether one of two random variables is stochastically larger than the other
    • D.R. Whitney H.B. Mann. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18:50-60.
    • (1947) Annals of Mathematical Statistics , vol.18 , pp. 50-60
    • Whitney, D.R.1    Mann, H.B.2
  • 29
    • 33645762226 scopus 로고
    • A sharper bonferroni procedure for multiple tests of significance
    • Y. Hochberg. (1988). A sharper bonferroni procedure for multiple tests of significance. Biometrika, 75:800-803.
    • (1988) Biometrika , vol.75 , pp. 800-803
    • Hochberg, Y.1
  • 30
    • 0002294347 scopus 로고
    • A simple sequentially rejective multiple test procedure
    • S. Holm. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6:65-70.
    • (1979) Scandinavian Journal of Statistics , vol.6 , pp. 65-70
    • Holm, S.1
  • 31
    • 0001750957 scopus 로고
    • Approximations of the critical region of the friedman statistic
    • R.L. Iman and J.M. Davenport. (1980). Approximations of the critical region of the friedman statistic. Communications in Statistics, 9:571-595.
    • (1980) Communications in Statistics , vol.9 , pp. 571-595
    • Iman, R.L.1    Davenport, J.M.2
  • 32
    • 60249094201 scopus 로고    scopus 로고
    • A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and nonparametric tests
    • J. Luengo, S. García, and F. Herrera. (2009). A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and nonparametric tests. Expert Systems with Applications, 36:7798-7808.
    • (2009) Expert Systems with Applications , vol.36 , pp. 7798-7808
    • Luengo, J.1    García, S.2    Herrera, F.3
  • 33
    • 50549085684 scopus 로고    scopus 로고
    • SGERD: A steady-state genetic algorithm for extracting fuzzy classification rules from data
    • E.G. Mansoori, M.J. Zolghadri, and S.D. Katebi. (2008). SGERD: A steady-state genetic algorithm for extracting fuzzy classification rules from data. IEEE Transactions on Fuzzy Systems, 16(4):1061-1071.
    • (2008) IEEE Transactions on Fuzzy Systems , vol.16 , Issue.4 , pp. 1061-1071
    • Mansoori, E.G.1    Zolghadri, M.J.2    Katebi, S.D.3
  • 36
    • 0036670786 scopus 로고    scopus 로고
    • Data mining with an ant colony optimization algorithm
    • DOI 10.1109/TEVC.2002.802452, PII 1011092002802452
    • R.S. Parpinelli, H.S. Lopes, and A.A. Freitas. (2002). Data mining with an ant colony optimization algorithm. IEEE Transactions on Evolutionary Computation, 6(4):321-332. (Pubitemid 35032734)
    • (2002) IEEE Transactions on Evolutionary Computation , vol.6 , Issue.4 , pp. 321-332
    • Parpinelli, R.S.1    Lopes, H.S.2    Freitas, A.A.3
  • 37
    • 34548230003 scopus 로고    scopus 로고
    • Advocating the use of imprecisely observed data in genetic fuzzy systems
    • DOI 10.1109/TFUZZ.2007.895942
    • L. Sánchez and I. Couso. (2007). Advocating the use of imprecisely observed data in genetic fuzzy systems. IEEE Transactions on Fuzzy Systems, 15(4):551-562. (Pubitemid 47316709)
    • (2007) IEEE Transactions on Fuzzy Systems , vol.15 , Issue.4 , pp. 551-562
    • Sanchez, L.1    Couso, I.2
  • 40
    • 0000898845 scopus 로고
    • An analysis of variance test for normality (complete samples)
    • M.B. Wilk S.S. Shapiro. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4):591-611.
    • (1965) Biometrika , vol.52 , Issue.3-4 , pp. 591-611
    • Wilk, M.B.1    Shapiro, S.S.2
  • 42
    • 33749017627 scopus 로고    scopus 로고
    • A coevolutionary algorithm for rules discovery in data mining
    • DOI 10.1080/00207720600879641, PII JT8764N807638221
    • K. C. Tan, Q.Yu, and J. H. Ang. (2006). A coevolutionary algorithm for rules discovery in data mining. International Journal of Systems Science, 37(12):835-864. (Pubitemid 44451664)
    • (2006) International Journal of Systems Science , vol.37 , Issue.12 , pp. 835-864
    • Tan, K.C.1    Yu, Q.2    Ang, J.H.3
  • 43
    • 35748982409 scopus 로고    scopus 로고
    • JCLEC: A Java framework for evolutionary computation
    • DOI 10.1007/s00500-007-0172-0, Special issue (pp 315-357) "Ordered structures in many-valued logic"
    • S. Ventura, C. Romero, A. Zafra, J.A. Delgado, and C. Hervás. (2008). Jclec: A java framework for evolutionary computation. Soft Computing, 12(4):381-392. (Pubitemid 350041999)
    • (2008) Soft Computing , vol.12 , Issue.4 , pp. 381-392
    • Ventura, S.1    Romero, C.2    Zafra, A.3    Delgado, J.A.4    Hervas, C.5
  • 44
    • 0001884644 scopus 로고
    • Individual comparisons by ranking methods
    • F.Wilcoxon. (1945). Individual comparisons by ranking methods. Biometrics, 1:80-83.
    • (1945) Biometrics , vol.1 , pp. 80-83
    • Wilcoxon, F.1
  • 47
    • 0027057407 scopus 로고
    • Adjusted P-values for simultaneous inference
    • S. P. Wright. (1992). Adjusted p-values for simultaneous inference. Biometrics, 48:1005-1013. (Pubitemid 23066474)
    • (1992) Biometrics , vol.48 , Issue.4 , pp. 1005-1013
    • Wright, S.P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.