메뉴 건너뛰기




Volumn 20, Issue 2, 2012, Pages 249-275

Resampling methods for meta-model validation with recommendations for evolutionary computation

Author keywords

Evolutionary computation; Evolutionary optimization; Meta models; Model validation; Regression; Resampling

Indexed keywords

EVOLUTIONARY OPTIMIZATIONS; META MODEL; MODEL VALIDATION; REGRESSION; RESAMPLING;

EID: 84860796007     PISSN: 10636560     EISSN: 15309304     Source Type: Journal    
DOI: 10.1162/EVCO_a_00069     Document Type: Article
Times cited : (147)

References (71)
  • 1
    • 0033570831 scopus 로고    scopus 로고
    • Combined 5 × 2CV F test for comparing supervised classification learning algorithms
    • Alpaydin, E. (1999). Combined 5 × 2CV F test for comparing supervised classification learning algorithms. Neural Computation, 11:1885-1892.
    • (1999) Neural Computation , vol.11 , pp. 1885-1892
    • Alpaydin, E.1
  • 2
    • 0036643049 scopus 로고    scopus 로고
    • Model selection and error estimation
    • Bartlett, P., Boucheron, S., and Lugosi, G. (2002). Model selection and error estimation. Machine Learning, 48(1-3):85-113.
    • (2002) Machine Learning , vol.48 , Issue.1-3 , pp. 85-113
    • Bartlett, P.1    Boucheron, S.2    Lugosi, G.3
  • 4
    • 84925604888 scopus 로고    scopus 로고
    • No unbiased estimator of the variance of k-fold cross-validation
    • Bengio, Y., and Grandvalet, Y. (2004). No unbiased estimator of the variance of k-fold cross-validation. Journal of Machine Learning Research, 5:1089-1105.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 1089-1105
    • Bengio, Y.1    Grandvalet, Y.2
  • 6
    • 48849102758 scopus 로고    scopus 로고
    • Adapting prediction error estimates for biased complexity selection in high-dimensional bootstrap samples
    • Binder, H., and Schumacher, M. (2008). Adapting prediction error estimates for biased complexity selection in high-dimensional bootstrap samples. Statistical Applications in Genetics and Molecular Biology, 7(1):12.
    • (2008) Statistical Applications In Genetics and Molecular Biology , vol.7 , Issue.1 , pp. 12
    • Binder, H.1    Schumacher, M.2
  • 8
    • 84860822696 scopus 로고    scopus 로고
    • MLR: Machine learning in R
    • Bischl, B. (2010). MLR: Machine learning in R. Retrieved from http://mlr.r-forge.r-project.org
    • (2010) Retrieved From
    • Bischl, B.1
  • 9
    • 18544390529 scopus 로고    scopus 로고
    • Accelerating evolutionary algorithms with Gaussian process fitness function models. IEEE Transactions on Systems
    • B üche, D., Schraudolph, N. N., and Koumoutsakos, P. (2004). Accelerating evolutionary algorithms with Gaussian process fitness function models. IEEE Transactions on Systems, Man and Cybernetics, 35:183-194.
    • (2004) Man and Cybernetics , vol.35 , pp. 183-194
    • Büche, D.1    Schraudolph, N.N.2    Koumoutsakos, P.3
  • 10
    • 8444241860 scopus 로고    scopus 로고
    • Fast exact leave-one-out cross-validation of sparse least-squares support vector machines
    • Cawley, G., and Talbot, N. (2004). Fast exact leave-one-out cross-validation of sparse least-squares support vector machines. Neural Networks, 17(10):1467-1475.
    • (2004) Neural Networks , vol.17 , Issue.10 , pp. 1467-1475
    • Cawley, G.1    Talbot, N.2
  • 11
    • 0033903664 scopus 로고    scopus 로고
    • Unsupervised stratification of cross-validation for accuracy estimation
    • Diamantidis, N., Karlis, D., and Giakoumakis, E. (2000). Unsupervised stratification of cross-validation for accuracy estimation. Artificial Intelligence, 116(1-2):1-16.
    • (2000) Artificial Intelligence , vol.116 , Issue.1-2 , pp. 1-16
    • Diamantidis, N.1    Karlis, D.2    Giakoumakis, E.3
  • 12
    • 0000259511 scopus 로고    scopus 로고
    • Approximate statistical tests for comparing supervised classification learning algorithms
    • Dietterich, T. (1998). Approximate statistical tests for comparing supervised classification learning algorithms. Neural Computation, 10(7):1895-1923.
    • (1998) Neural Computation , vol.10 , Issue.7 , pp. 1895-1923
    • Dietterich, T.1
  • 13
    • 0002344794 scopus 로고
    • Bootstrap methods: Another look at the jackknife
    • Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1):1-26.
    • (1979) The Annals of Statistics , vol.7 , Issue.1 , pp. 1-26
    • Efron, B.1
  • 14
    • 84950461478 scopus 로고
    • Estimating the error rate of a prediction rule: Improvement on cross-validation
    • Efron, B. (1983). Estimating the error rate of a prediction rule: Improvement on cross-validation. Journal of the American Statistical Association, 78(382):316-331.
    • (1983) Journal of the American Statistical Association , vol.78 , Issue.382 , pp. 316-331
    • Efron, B.1
  • 15
    • 0031536511 scopus 로고    scopus 로고
    • Improvements on cross-validation: The 0.632 + bootstrap method
    • Efron, B., and Tibshirani, R. (1997). Improvements on cross-validation: The 0.632 + bootstrap method. Journal of the American Statistical Association, 92(438):548-560.
    • (1997) Journal of the American Statistical Association , vol.92 , Issue.438 , pp. 548-560
    • Efron, B.1    Tibshirani, R.2
  • 16
    • 0002589996 scopus 로고    scopus 로고
    • Metamodeling techniques for evolutionary optimization of computationally expensive problems: Promises and limitations
    • El-Beltagy, M., Nair, P. B., and Keane, A. J. (1999). Metamodeling techniques for evolutionary optimization of computationally expensive problems: Promises and limitations. In Genetic and Evolutionary Computation Conference (GECCO), pp. 196-203.
    • (1999) In Genetic and Evolutionary Computation Conference (GECCO) , pp. 196-203
    • El-Beltagy, M.1    Nair, P.B.2    Keane, A.J.3
  • 17
    • 33747424045 scopus 로고    scopus 로고
    • Single-and multiobjective evolutionary optimization assisted by Gaussian random field metamodels
    • Emmerich, M., Giannakoglou, K., and Naujoks, B. (2006). Single-and multiobjective evolutionary optimization assisted by Gaussian random field metamodels. IEEE Transactions on Evolutionary Computation, 10(4):421-439.
    • (2006) IEEE Transactions On Evolutionary Computation , vol.10 , Issue.4 , pp. 421-439
    • Emmerich, M.1    Giannakoglou, K.2    Naujoks, B.3
  • 19
    • 18744413287 scopus 로고    scopus 로고
    • Estimating misclassification error with small samples via bootstrap cross-validation
    • Fu, W. J., Carroll, R. J., and Wang, S. (2005). Estimating misclassification error with small samples via bootstrap cross-validation. Bioinformatics, 21(9):1979-1986.
    • (2005) Bioinformatics , vol.21 , Issue.9 , pp. 1979-1986
    • Fu, W.J.1    Carroll, R.J.2    Wang, S.3
  • 24
    • 33644791173 scopus 로고    scopus 로고
    • Global optimization of stochastic black-box systems via sequential Kriging meta-models
    • Huang, D., Allen, T., Notz, W., and Zeng, N. (2006). Global optimization of stochastic black-box systems via sequential Kriging meta-models. Journal of Global Optimization, 34(3):441-466.
    • (2006) Journal of Global Optimization , vol.34 , Issue.3 , pp. 441-466
    • Huang, D.1    Allen, T.2    Notz, W.3    Zeng, N.4
  • 25
    • 0035727744 scopus 로고    scopus 로고
    • Comparative studies of metamodeling techniques under multiple modeling criteria
    • Jin, R., Chen, W., and Simpson, T. (2000). Comparative studies of metamodeling techniques under multiple modeling criteria. Structural and Multidisciplinary Optimization, 23:1-13.
    • (2000) Structural and Multidisciplinary Optimization , vol.23 , pp. 1-13
    • Jin, R.1    Chen, W.2    Simpson, T.3
  • 26
    • 21144433756 scopus 로고    scopus 로고
    • A comprehensive survey of fitness approximation in evolutionary computation
    • Jin, Y. (2005). A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing, 9(1):3-12.
    • (2005) Soft Computing , vol.9 , Issue.1 , pp. 3-12
    • Jin, Y.1
  • 27
    • 21044438483 scopus 로고    scopus 로고
    • Evolutionary optimization in uncertain environments: A survey
    • Jin, Y., and Brank, J. (2005). Evolutionary optimization in uncertain environments: A survey. IEEE Transactions on Evolutionary Computation, 9(3):303-318.
    • (2005) IEEE Transactions On Evolutionary Computation , vol.9 , Issue.3 , pp. 303-318
    • Jin, Y.1    Brank, J.2
  • 29
  • 30
    • 0000561424 scopus 로고    scopus 로고
    • Efficient global optimization of expensive black-box functions
    • Jones, D., Schonlau, M., and Welch, W. (1998). Efficient global optimization of expensive black-box functions. Journal of Global Optimization, 13(4):455-492.
    • (1998) Journal of Global Optimization , vol.13 , Issue.4 , pp. 455-492
    • Jones, D.1    Schonlau, M.2    Welch, W.3
  • 31
    • 79955289884 scopus 로고    scopus 로고
    • Multilevel optimization strategies based on metamodel-assisted evolutionary algorithms, for computationally expensive problems
    • In K. C. Tan and J.-X. Xu (Eds.)
    • Kampolis, I. C., Zymaris, A. S., Asouti, V. G., and Giannakoglou, K. C. (2007). Multilevel optimization strategies based on metamodel-assisted evolutionary algorithms, for computationally expensive problems. In K. C. Tan and J.-X. Xu (Eds.), IEEE Congress on Evolutionary Computation (CEC), pp. 4116-4123.
    • (2007) IEEE Congress On Evolutionary Computation (CEC) , pp. 4116-4123
    • Kampolis, I.C.1    Zymaris, A.S.2    Asouti, V.G.3    Giannakoglou, K.C.4
  • 33
    • 65749119811 scopus 로고    scopus 로고
    • Estimating classification error rate: Repeated cross-validation, repeated holdout and bootstrap
    • Kim, J.-H. (2009). Estimating classification error rate: Repeated cross-validation, repeated holdout and bootstrap. Computational Statistics and Data Analysis, 53(11):3735-3745.
    • (2009) Computational Statistics and Data Analysis , vol.53 , Issue.11 , pp. 3735-3745
    • Kim, J.H.1
  • 35
    • 85164392958 scopus 로고
    • A study of cross-validation and bootstrap for accuracy estimation and model selection
    • Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 1137-1143.
    • (1995) International Joint Conference On Artificial Intelligence (IJCAI) , pp. 1137-1143
    • Kohavi, R.1
  • 41
    • 25144494760 scopus 로고    scopus 로고
    • Prediction error estimation: A comparison of resampling methods
    • Molinaro, A., Simon, R., and Pfeiffer, R. (2005). Prediction error estimation: A comparison of resampling methods. Bioinformatics, 21(15):3301-3307.
    • (2005) Bioinformatics , vol.21 , Issue.15 , pp. 3301-3307
    • Molinaro, A.1    Simon, R.2    Pfeiffer, R.3
  • 44
    • 0042847140 scopus 로고    scopus 로고
    • Inference for the generalization error
    • Nadeau, C., and Bengio, Y. (2003). Inference for the generalization error. Machine Learning, 52(3):239-281.
    • (2003) Machine Learning , vol.52 , Issue.3 , pp. 239-281
    • Nadeau, C.1    Bengio, Y.2
  • 46
    • 0037394089 scopus 로고    scopus 로고
    • Evolutionary optimization of computationally expensive problems via surrogate modeling
    • Ong, Y., Nair, P., and Keane, A. (2003). Evolutionary optimization of computationally expensive problems via surrogate modeling. AIAA Journal, 41(4):687-696.
    • (2003) AIAA Journal , vol.41 , Issue.4 , pp. 687-696
    • Ong, Y.1    Nair, P.2    Keane, A.3
  • 47
    • 34248664099 scopus 로고    scopus 로고
    • Curse and blessing of uncertainty in evolutionary algorithms using approximation
    • Ong, Y., Zhou, Z., and Lim, D. (2006). Curse and blessing of uncertainty in evolutionary algorithms using approximation. In IEEE Congress on Evolutionary Computation (CEC), pp. 2928-2935.
    • (2006) In IEEE Congress On Evolutionary Computation (CEC) , pp. 2928-2935
    • Ong, Y.1    Zhou, Z.2    Lim, D.3
  • 48
    • 33747417835 scopus 로고    scopus 로고
    • Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation
    • Paenke, I., Branke, J., and Jin, Y. (2006). Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation. IEEE Transactions on Evolutionary Computation, 10(4):405-420.
    • (2006) IEEE Transactions On Evolutionary Computation , vol.10 , Issue.4 , pp. 405-420
    • Paenke, I.1    Branke, J.2    Jin, Y.3
  • 49
    • 27144463192 scopus 로고    scopus 로고
    • On comparing classifiers: Pitfalls to avoid and a recommended approach
    • Salzberg, S. (1997). On comparing classifiers: Pitfalls to avoid and a recommended approach. Data Mining and Knowledge Discovery, 1(3):317-328.
    • (1997) Data Mining and Knowledge Discovery , vol.1 , Issue.3 , pp. 317-328
    • Salzberg, S.1
  • 50
    • 49049096322 scopus 로고    scopus 로고
    • Toward an optimal ensemble of kernel-based approximations with engineering applications
    • Sanchez, E., Pintos, S., and Queipo, N. (2008). Toward an optimal ensemble of kernel-based approximations with engineering applications. Structural and Multidisciplinary Optimization, 36(3):247-261.
    • (2008) Structural and Multidisciplinary Optimization , vol.36 , Issue.3 , pp. 247-261
    • Sanchez, E.1    Pintos, S.2    Queipo, N.3
  • 52
  • 54
    • 77951294020 scopus 로고    scopus 로고
    • Resampling strategies for model assessment and selection
    • Berlin: Springer
    • Simon, R. (2007). Resampling strategies for model assessment and selection. In Fundamentals of data mining in genomics and proteomics (pp. 173-186). Berlin: Springer.
    • (2007) Fundamentals of Data Mining In Genomics and Proteomics , pp. 173-186
    • Simon, R.1
  • 55
    • 0037245343 scopus 로고    scopus 로고
    • Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification
    • Simon, R., Radmacher, M. D., Dobbin, K., and McShane, L. M. (2003). Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. Journal of the National Cancer Institute, 95(1):14-18.
    • (2003) Journal of the National Cancer Institute , vol.95 , Issue.1 , pp. 14-18
    • Simon, R.1    Radmacher, M.D.2    Dobbin, K.3    McShane, L.M.4
  • 57
    • 70449814748 scopus 로고    scopus 로고
    • Comparing parameter tuning methods for evolutionary algorithms
    • In A. Tyrrell (Ed.)
    • Smit, S., and Eiben, A. (2009). Comparing parameter tuning methods for evolutionary algorithms. In A. Tyrrell (Ed.), IEEE Congress on Evolutionary Computation (CEC), pp. 399-406.
    • (2009) IEEE Congress On Evolutionary Computation (CEC) , pp. 399-406
    • Smit, S.1    Eiben, A.2
  • 58
    • 0000629975 scopus 로고
    • Cross-validatory choice and assessment of statistical predictions
    • Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, Series B, 36(1):111-147.
    • (1974) Journal of the Royal Statistical Society, Series B , vol.36 , Issue.1 , pp. 111-147
    • Stone, M.1
  • 59
    • 0000859675 scopus 로고
    • An asymptotic equivalence of choice of model by cross-validation and Akaike's criterion
    • Stone, M. (1977). An asymptotic equivalence of choice of model by cross-validation and Akaike's criterion. Journal of the Royal Statistical Society, Series B, 39:44-47.
    • (1977) Journal of the Royal Statistical Society, Series B , vol.39 , pp. 44-47
    • Stone, M.1
  • 60
    • 0035344742 scopus 로고    scopus 로고
    • Predictive approaches for choosing hyperparameters in Gaussian processes
    • Sundararajan, S., and Keerthi, S. (2001). Predictive approaches for choosing hyperparameters in Gaussian processes. Neural Computation, 13(5):1103-1118.
    • (2001) Neural Computation , vol.13 , Issue.5 , pp. 1103-1118
    • Sundararajan, S.1    Keerthi, S.2
  • 62
    • 84901437141 scopus 로고    scopus 로고
    • Evolution strategies assisted by Gaussian processes with improved pre-selection criterion
    • Ulmer, H., Streichert, F., and Zell, A. (2003). Evolution strategies assisted by Gaussian processes with improved pre-selection criterion. In IEEE Congress on Evolutionary Computation (CEC), pp. 692-699.
    • (2003) IEEE Congress On Evolutionary Computation (CEC) , pp. 692-699
    • Ulmer, H.1    Streichert, F.2    Zell, A.3
  • 63
    • 77954583319 scopus 로고    scopus 로고
    • Better solutions faster: Soft evolution of robust regression models in Pareto genetic programming
    • In R. L. Riolo, T. Soule, and B. Worzel (Eds.), Berlin: Springer
    • Vladislavleva, E., Smits, G., and Kotanchek, M. (2007). Better solutions faster: Soft evolution of robust regression models in Pareto genetic programming. In R. L. Riolo, T. Soule, and B. Worzel (Eds.), Genetic programming theory and practice V, Genetic and evolutionary computation (chap. 2, pp. 13-32). Berlin: Springer.
    • (2007) Genetic Programming Theory and Practice V, Genetic and Evolutionary Computation (chap , vol.2 , pp. 13-32
    • Vladislavleva, E.1    Smits, G.2    Kotanchek, M.3
  • 64
    • 78149266813 scopus 로고    scopus 로고
    • On expected-improvement criteria for model-based multi-objective optimization
    • In R. Schaefer (Ed.)
    • Wagner, T., Emmerich, M., Deutz, A., and Ponweiser, W. (2010). On expected-improvement criteria for model-based multi-objective optimization. In R. Schaefer (Ed.), Parallel Problem Solving from Nature (PPSN), pp. 718-727.
    • (2010) Parallel Problem Solving From Nature (PPSN) , pp. 718-727
    • Wagner, T.1    Emmerich, M.2    Deutz, A.3    Ponweiser, W.4
  • 65
    • 0005173689 scopus 로고
    • Spline bases, regularization, and generalized cross validation for solving approximation problems with large quantities of noisy data
    • Wahba, G. (1980). Spline bases, regularization, and generalized cross validation for solving approximation problems with large quantities of noisy data. In International Conference on Approximation Theory in Honour of George Lorenz.
    • (1980) International Conference On Approximation Theory In Honour of George Lorenz
    • Wahba, G.1
  • 66
    • 84860794903 scopus 로고
    • Canonical discriminant analysis: Comparison of resampling methods and convex-hull approximation
    • Berlin: Springer
    • Weihs, C. (1993). Canonical discriminant analysis: Comparison of resampling methods and convex-hull approximation. Information and Classification (pp. 225-238). Berlin: Springer.
    • (1993) Information and Classification , pp. 225-238
    • Weihs, C.1
  • 68
    • 0001673027 scopus 로고
    • Jackknife, bootstrap and other resampling methods in regression analysis
    • Wu, C. (1986). Jackknife, bootstrap and other resampling methods in regression analysis. Annals of Statistics, 14:1261-1295.
    • (1986) Annals of Statistics , vol.14 , pp. 1261-1295
    • Wu, C.1
  • 69
    • 77952358730 scopus 로고    scopus 로고
    • Metamodelling using search space exploration and unimodal region elimination for design optimization
    • Younis, A., and Dong, Z. (2010). Metamodelling using search space exploration and unimodal region elimination for design optimization. Engineering Optimization, 6(42):517-533.
    • (2010) Engineering Optimization , vol.6 , Issue.42 , pp. 517-533
    • Younis, A.1    Dong, Z.2
  • 70
    • 81155147828 scopus 로고    scopus 로고
    • Multi-objective optimisation based on meta-modelling using support vector regression
    • Yun, Y., Yoon, M., and Nakayama, H. (2009). Multi-objective optimisation based on meta-modelling using support vector regression. Optimization and Engineering, 10(2):167-181.
    • (2009) Optimization and Engineering , vol.10 , Issue.2 , pp. 167-181
    • Yun, Y.1    Yoon, M.2    Nakayama, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.