메뉴 건너뛰기




Volumn 23, Issue 8, 2009, Pages 1527-1548

Diagnose effective evolutionary prototype selection using an overlapping measure

Author keywords

Complexity measures; Data complexity; Evolutionary prototype selection; Overlapping measure; Prototype selection

Indexed keywords

SOFTWARE ENGINEERING;

EID: 74549133500     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001409007727     Document Type: Article
Times cited : (19)

References (37)
  • 1
    • 25444531678 scopus 로고    scopus 로고
    • Decision boundary preserving prototype selection for nearest neighbor classification
    • R. Barandela, F. J. Ferri and J. S. Śanchez, Decision boundary preserving prototype selection for nearest neighbor classification, Int. J. Patt. Recogn. Artif. Intell. 19(6) (2005) 787-806.
    • (2005) Int. J. Patt. Recogn. Artif. Intell. , vol.19 , Issue.6 , pp. 787-806
    • Barandela, R.1    Ferri, F.J.2    Śanchez, J.S.3
  • 3
    • 33646808651 scopus 로고    scopus 로고
    • Data complexity assessment in undersampled classification of high-dimensional biomedical data
    • R. Baumgartner and R. L. Somorjai, Data complexity assessment in undersampled classification of high-dimensional biomedical data, Patt. Recogn. Lett. 27(12) (2006) 1383-1389.
    • (2006) Patt. Recogn. Lett. , vol.27 , Issue.12 , pp. 1383-1389
    • Baumgartner, R.1    Somorjai, R.L.2
  • 4
    • 14844318559 scopus 로고    scopus 로고
    • Domain of competence of XCS classifier system in complexity measurement space
    • E. Bernad́o-Mansilla and T. K. Ho, Domain of competence of XCS classifier system in complexity measurement space, IEEE Trans. Evolut. Comput. 9(1) (2005) 82-104.
    • (2005) IEEE Trans. Evolut. Comput. , vol.9 , Issue.1 , pp. 82-104
    • Bernad́o-Mansilla, E.1    Ho, T.K.2
  • 5
    • 0347763609 scopus 로고    scopus 로고
    • Using evolutionary computation as instance selection for data reduction in KDD: An experimental study
    • J.-R. Cano, F. Herrera and M. Lozano, Using evolutionary computation as instance selection for data reduction in KDD: An experimental study, IEEE Trans. Evolut. Comput. 7(6) (2003) 561-575.
    • (2003) IEEE Trans. Evolut. Comput. , vol.7 , Issue.6 , pp. 561-575
    • Cano, J.-R.1    Herrera, F.2    Lozano, M.3
  • 7
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparison of classifiers over multiple data sets
    • J. Demsar, Statistical comparison of classifiers over multiple data sets, J. Mach. Learn. Res. 7 (2006) 1-30.
    • (2006) J. Mach. Learn. Res. , vol.7 , pp. 1-30
    • Demsar, J.1
  • 8
    • 0037410630 scopus 로고    scopus 로고
    • Feature subset selection using a new definition of classifiability
    • M. Dong and R. Kothari, Feature subset selection using a new definition of classifiability, Patt. Recogn. Lett. 24(9-10) (2003) 1215-1225.
    • (2003) Patt. Recogn. Lett. , vol.24 , Issue.9-10 , pp. 1215-1225
    • Dong, M.1    Kothari, R.2
  • 10
    • 0001334115 scopus 로고
    • The CHC adaptive search algorithm: How to have safe search when engaging in nontraditional genetic recombination
    • 1, ed. G. J. E. Rawlins Morgan Kauffman
    • L. J. Eshelman, The CHC adaptive search algorithm: How to have safe search when engaging in nontraditional genetic recombination, in Foundations of Genetic Algorithms 1, ed. G. J. E. Rawlins (Morgan Kauffman, 1991), pp. 265-283.
    • (1991) Foundations of Genetic Algorithms , pp. 265-283
    • Eshelman, L.J.1
  • 12
    • 70349617264 scopus 로고    scopus 로고
    • Evolutionary under-sampling for classification with imbalanced data sets: Proposals and taxonomy
    • S. Garćia and F. Herrera, Evolutionary under-sampling for classification with imbalanced data sets: Proposals and taxonomy, Evolut. Comput. 17(3) (2008) 275-306.
    • (2008) Evolut. Comput. , vol.17 , Issue.3 , pp. 275-306
    • Garćia, S.1    Herrera, F.2
  • 13
    • 58149287952 scopus 로고    scopus 로고
    • An extension on statistical comparisons of classifiers over multiple data sets for all pairwise comparisons
    • S. Garćia and F. Herrera, An extension on statistical comparisons of classifiers over multiple data sets for all pairwise comparisons, J. Mach. Learn. Res. 9 (2008) 2677-2694.
    • (2008) J. Mach. Learn. Res. , vol.9 , pp. 2677-2694
    • Garćia, S.1    Herrera, F.2
  • 14
    • 64549120231 scopus 로고    scopus 로고
    • A study of statistical techniques and performance measures for genetics-based machine learning: Accuracy and interpretability
    • S. Garćia, A. Ferńandez, J. Luengo and F. Herrera, A study of statistical techniques and performance measures for genetics-based machine learning: Accuracy and interpretability, Soft Comput. 13(10) (2009) 959-977.
    • (2009) Soft Comput. , vol.13 , Issue.10 , pp. 959-977
    • Garćia, S.1    Ferńandez, A.2    Luengo, J.3    Herrera, F.4
  • 16
    • 9444268167 scopus 로고    scopus 로고
    • Comparison of instance selection algorithms II. Results and comments
    • Lecture Notes in Computer Science
    • M. Grochowski and N. Jankowski, Comparison of instance selection algorithms II. Results and comments, Proc. 7th Int. Conf. Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science, Vol.3070 (2004), pp. 580-585.
    • (2004) Proc. 7th Int. Conf. Artificial Intelligence and Soft Computing , vol.3070 , pp. 580-585
    • Grochowski, M.1    Jankowski, N.2
  • 17
    • 84931162639 scopus 로고
    • The condensed nearest neighbor rule
    • P. E. Hart, The condensed nearest neighbor rule, IEEE Trans. Inform. Th. 14 (1968) 515-516.
    • (1968) IEEE Trans. Inform. Th. , vol.14 , pp. 515-516
    • Hart, P.E.1
  • 18
    • 0031249331 scopus 로고    scopus 로고
    • Large-scale simulation studies in image pattern recognition
    • T. K. Ho and H. S. Baird, Large-scale simulation studies in image pattern recognition, IEEE Trans. Patt. Anal. Mach. Intell. 19(10) (1997) 1067-1079.
    • (1997) IEEE Trans. Patt. Anal. Mach. Intell. , vol.19 , Issue.10 , pp. 1067-1079
    • Ho, T.K.1    Baird, H.S.2
  • 19
    • 0036522441 scopus 로고    scopus 로고
    • Complexity measures of supervised classification problems
    • T. K. Ho and M. Basu, Complexity measures of supervised classification problems, IEEE Trans. Patt. Anal. Mach. Intell. 24(3) (2002) 289-300.
    • (2002) IEEE Trans. Patt. Anal. Mach. Intell. , vol.24 , Issue.3 , pp. 289-300
    • Ho, T.K.1    Basu, M.2
  • 20
    • 0037404505 scopus 로고    scopus 로고
    • Enhancing prototype reduction schemes with LVQ3- type algorithms
    • S. W. Kim and B. J. Oommen, Enhancing prototype reduction schemes with LVQ3- type algorithms, Patt. Recogn. 36 (2004) 1083-1093.
    • (2004) Patt. Recogn. , vol.36 , pp. 1083-1093
    • Kim, S.W.1    Oommen, B.J.2
  • 21
    • 0242539900 scopus 로고    scopus 로고
    • On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods
    • S. W. Kim and B. J. Oommen, On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods, Patt. Recogn. 37 (2004) 227-239.
    • (2004) Patt. Recogn. , vol.37 , pp. 227-239
    • Kim, S.W.1    Oommen, B.J.2
  • 22
    • 0000935031 scopus 로고
    • Editing for the k-nearest neighbors rule by a genetic algorithm
    • L. Kuncheva, Editing for the k-nearest neighbors rule by a genetic algorithm, Patt. Recogn. Lett. 16 (1995) 809-814.
    • (1995) Patt. Recogn. Lett. , vol.16 , pp. 809-814
    • Kuncheva, L.1
  • 23
    • 28244495034 scopus 로고    scopus 로고
    • Classifiability-based omnivariate decision trees
    • Y.-H. Li, M. Dong and R. Kothari, Classifiability-based omnivariate decision trees, IEEE Trans. Neural Networks 16(6) (2005) 1547-1560.
    • (2005) IEEE Trans. Neural Networks , vol.16 , Issue.6 , pp. 1547-1560
    • Li, Y.-H.1    Dong, M.2    Kothari, R.3
  • 24
    • 33847342089 scopus 로고    scopus 로고
    • Handwriting recognition of whiteboard notes - Studying the influence of training set size and type
    • M. Liwicki and H. Bunke, Handwriting recognition of whiteboard notes - studying the influence of training set size and type, Int. J. Patt. Recogn. Artif. Intell. 21(1) (2007) 83-98.
    • (2007) Int. J. Patt. Recogn. Artif. Intell. , vol.21 , Issue.1 , pp. 83-98
    • Liwicki, M.1    Bunke, H.2
  • 25
    • 25144505553 scopus 로고    scopus 로고
    • Data characterization for effective prototype selection
    • Lecture Notes in Computer Science
    • R. A. Mollineda, J. S. Śanchez and J. M. Sotoca, Data characterization for effective prototype selection, Proc. IbPRIA 2005, Lecture Notes in Computer Science, Vol.3523 (2005), pp. 27-34.
    • Proc. IbPRIA 2005 , vol.3523 , Issue.2005 , pp. 27-34
    • Mollineda, R.A.1    Śanchez, J.S.2    Sotoca, J.M.3
  • 26
    • 36948999941 scopus 로고    scopus 로고
    • Irvine, CA: University of California, Schools of Information and Computer Science
    • A. Asuncion and D. J. Newman, UCI Machine Learning Repository [http://www. ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, Schools of Information and Computer Science, 2007.
    • (2007) UCI Machine Learning Repository
    • Asuncion, A.1    Newman, D.J.2
  • 29
    • 33845801750 scopus 로고    scopus 로고
    • Nearest neighbor discriminant analysis
    • X. Qiu and L. Wu, Nearest neighbor discriminant analysis, Int. J. Patt. Recogn. Artif. Intell. 20(8) (2006) 1245-1259.
    • (2006) Int. J. Patt. Recogn. Artif. Intell. , vol.20 , Issue.8 , pp. 1245-1259
    • Qiu, X.1    Wu, L.2
  • 30
    • 34547399424 scopus 로고    scopus 로고
    • An analysis of how training data complexity affects the nearest neighbors classifiers
    • J. S. Śanchez, R. A. Mollineda and J. M. Sotoca, An analysis of how training data complexity affects the nearest neighbors classifiers, Patt. Anal. Appl. 10 (2007) 189-201.
    • (2007) Patt. Anal. Appl. , vol.10 , pp. 189-201
    • Śanchez, J.S.1    Mollineda, R.A.2    Sotoca, J.M.3
  • 32
    • 0347379706 scopus 로고    scopus 로고
    • Multiresolution estimates of classification complexity
    • S. Singh, Multiresolution estimates of classification complexity, IEEE Trans. Patt. Anal. Mach. Intell. 25(12) (2003) 1534-1539.
    • (2003) IEEE Trans. Patt. Anal. Mach. Intell. , vol.25 , Issue.12 , pp. 1534-1539
    • Singh, S.1
  • 33
    • 0036832996 scopus 로고    scopus 로고
    • Design of an optimal nearest neighbor classifier using an intelligent genetic algorithm
    • H. Shinn-Ying, L. Chia-Cheng and L. Soundy, Design of an optimal nearest neighbor classifier using an intelligent genetic algorithm, Patt. Recogn. Lett. 23(13) (2002) 1495-1503.
    • (2002) Patt. Recogn. Lett. , vol.23 , Issue.13 , pp. 1495-1503
    • Shinn-Ying, H.1    Chia-Cheng, L.2    Soundy, L.3
  • 34
    • 0015361129 scopus 로고
    • Asymptotic properties of nearest neighbor rules using edited data
    • D.L. Wilson, Asymptotic properties of nearest neighbor rules using edited data, IEEE Trans. Syst. Man Cybern. 2(3) (1972) 408-421.
    • (1972) IEEE Trans. Syst. Man Cybern. , vol.2 , Issue.3 , pp. 408-421
    • Wilson, D.L.1
  • 35
    • 0343081513 scopus 로고    scopus 로고
    • Reduction techniques for instance-based learning algorithms
    • D. R. Wilson and T. R. Martinez, Reduction techniques for instance-based learning algorithms, Mach. Learn. 38 (2000) 257-268.
    • (2000) Mach. Learn. , vol.38 , pp. 257-268
    • Wilson, D.R.1    Martinez, T.R.2
  • 36
    • 34547765318 scopus 로고    scopus 로고
    • Distributed learning based on chips for classification with large-scale data set
    • B. Yang, X. Su and Y. Wang, Distributed learning based on chips for classification with large-scale data set, Int. J. Patt. Recogn. Artif. Intell. 21(5) (2007) 899-920.
    • (2007) Int. J. Patt. Recogn. Artif. Intell. , vol.21 , Issue.5 , pp. 899-920
    • Yang, B.1    Su, X.2    Wang, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.