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Volumn 325, Issue , 2015, Pages 288-299

Counter propagation auto-associative neural network based data imputation

Author keywords

Auto associative neural network; Counter propagation auto associative neural network (CPAANN); Data imputation; Grey system theory (GST)

Indexed keywords

BACKPROPAGATION; NETWORK ARCHITECTURE; SYSTEM THEORY;

EID: 84941569673     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2015.07.016     Document Type: Article
Times cited : (25)

References (97)
  • 3
    • 33748323158 scopus 로고    scopus 로고
    • QSAR study of anti-HIV HEPT analogues based on multi-objective genetic programming and counter-propagation neural network
    • M. Arakawa, K. Hasegawa, K. Funatsu QSAR study of anti-HIV HEPT analogues based on multi-objective genetic programming and counter-propagation neural network Chemo. Intell. Lab. Syst. 83 2006 91 98
    • (2006) Chemo. Intell. Lab. Syst. , vol.83 , pp. 91-98
    • Arakawa, M.1    Hasegawa, K.2    Funatsu, K.3
  • 4
    • 18744361851 scopus 로고    scopus 로고
    • Bayesian modeling of missing data in clinical research
    • P.C. Austin, M.D. Escobar Bayesian modeling of missing data in clinical research Comput. Statics Data Anal. 49 3 2005 821 836
    • (2005) Comput. Statics Data Anal. , vol.49 , Issue.3 , pp. 821-836
    • Austin, P.C.1    Escobar, M.D.2
  • 5
    • 84875231751 scopus 로고    scopus 로고
    • A hybrid method for imputation of missing vlaues using optimized fuzzy c-means with support vector regression and a genetic algorithm
    • B. Aydilek, A. Arslan A hybrid method for imputation of missing vlaues using optimized fuzzy c-means with support vector regression and a genetic algorithm Informat. Sci. 233 2013 25 35
    • (2013) Informat. Sci. , vol.233 , pp. 25-35
    • Aydilek, B.1    Arslan, A.2
  • 6
    • 69349099689 scopus 로고    scopus 로고
    • The Kohonen and CP-ANN toolbox: A collection of MATLAB modules for self-organizing maps and counterpropagation artificial neural networks
    • D. Ballabio, V. Consonni, R. Todeschini The Kohonen and CP-ANN toolbox: a collection of MATLAB modules for self-organizing maps and counterpropagation artificial neural networks Chemo. Intell. Lab. Syst. 98 2009 115 122
    • (2009) Chemo. Intell. Lab. Syst. , vol.98 , pp. 115-122
    • Ballabio, D.1    Consonni, V.2    Todeschini, R.3
  • 7
    • 34247546249 scopus 로고    scopus 로고
    • Characterization of the traditional Cypriot spirit Zivania by means of counterpropagation artificial neural networks
    • D. Ballabio, R. Kokkinofta, R. Todeschini, C.R. Theocharis Characterization of the traditional Cypriot spirit Zivania by means of counterpropagation artificial neural networks Chemo. Intell. Lab. Syst. 87 2007 52 58
    • (2007) Chemo. Intell. Lab. Syst. , vol.87 , pp. 52-58
    • Ballabio, D.1    Kokkinofta, R.2    Todeschini, R.3    Theocharis, C.R.4
  • 8
    • 78650937098 scopus 로고    scopus 로고
    • Genetic algorithms for architecture optimisation of counter-propagation artificial neural networks
    • D. Ballabio, M. Vasighi, V. Consonni, M. Kompany-Zareh Genetic algorithms for architecture optimisation of counter-propagation artificial neural networks Chemom. Intell. Lab. Syst. 105 2011 56 64
    • (2011) Chemom. Intell. Lab. Syst. , vol.105 , pp. 56-64
    • Ballabio, D.1    Vasighi, M.2    Consonni, V.3    Kompany-Zareh, M.4
  • 11
    • 0043234660 scopus 로고    scopus 로고
    • Variable precision rough set theory and data discretisation: An application to corporate failure prediction
    • M.J. Beynon, M.J. Peel Variable precision rough set theory and data discretisation: an application to corporate failure prediction Omega 29 2001 561 576
    • (2001) Omega , vol.29 , pp. 561-576
    • Beynon, M.J.1    Peel, M.J.2
  • 12
    • 11144282042 scopus 로고    scopus 로고
    • Multivariate data analysis in classification of vegetable oils characterized by the content of fatty acids
    • D. Brodnjak-Vončina, J.C. Kodba, M. Novic Multivariate data analysis in classification of vegetable oils characterized by the content of fatty acids Chemom. Intell. Lab. Syst. 75 2005 31 43
    • (2005) Chemom. Intell. Lab. Syst. , vol.75 , pp. 31-43
    • Brodnjak-Vončina, D.1    Kodba, J.C.2    Novic, M.3
  • 13
    • 3142573361 scopus 로고    scopus 로고
    • Autoregressive spectral analysis when observations are missing
    • P. Broersen, S. de Waele, R. Bos Autoregressive spectral analysis when observations are missing Automatica 40 9 2004 1495 1504
    • (2004) Automatica , vol.40 , Issue.9 , pp. 1495-1504
    • Broersen, P.1    De Waele, S.2    Bos, R.3
  • 14
    • 13544271697 scopus 로고    scopus 로고
    • Prediction of commercial bank failure via multivariate statistical analysis of financial structures: The Turkish case
    • S. Canbas, A. Caubak, S.B. Kilic Prediction of commercial bank failure via multivariate statistical analysis of financial structures: the Turkish case Eur. J. Oper. Res. 166 2005 528 546
    • (2005) Eur. J. Oper. Res. , vol.166 , pp. 528-546
    • Canbas, S.1    Caubak, A.2    Kilic, S.B.3
  • 15
    • 0021776661 scopus 로고
    • A massively parallel architecture for a self-organizing neural pattern recognition machine
    • G. Carpenter, S. Grossberg A massively parallel architecture for a self-organizing neural pattern recognition machine Comput. Verion. Graph. Image Process. 37 1987 54 115
    • (1987) Comput. Verion. Graph. Image Process. , vol.37 , pp. 54-115
    • Carpenter, G.1    Grossberg, S.2
  • 16
    • 77957841216 scopus 로고    scopus 로고
    • Copyright authentication for images with a full counter-propagation neural network
    • C-Y. Chang, H-J. Wang, S-J. Su Copyright authentication for images with a full counter-propagation neural network Expert Syst. Appl. 37 12 2010 7639 7647
    • (2010) Expert Syst. Appl. , vol.37 , Issue.12 , pp. 7639-7647
    • Chang, C.-Y.1    Wang, H.-J.2    Su, S.-J.3
  • 17
    • 50949109918 scopus 로고    scopus 로고
    • A selective Bayes Classifier for classifying incomplete data based on gain ratio
    • J. Chen, H. Huang, F. Tian, S. Tian A selective Bayes Classifier for classifying incomplete data based on gain ratio Knowl. Based Syst. 21 7 2008 530 534
    • (2008) Knowl. Based Syst. , vol.21 , Issue.7 , pp. 530-534
    • Chen, J.1    Huang, H.2    Tian, F.3    Tian, S.4
  • 19
    • 0002629270 scopus 로고
    • Maximum-likelihood from incomplete data via the em algorithm
    • P. Dempster, N.M. Laird, D.B. Rubin Maximum-likelihood from incomplete data via the EM algorithm J. Roy. Stat. Soc. 39 1 1977 1 38
    • (1977) J. Roy. Stat. Soc. , vol.39 , Issue.1 , pp. 1-38
    • Dempster, P.1    Laird, N.M.2    Rubin, D.B.3
  • 20
    • 50849151631 scopus 로고
    • Control problems of grey system
    • J.L. Deng Control problems of grey system Syst. Control Lett. 1 1982 288 294
    • (1982) Syst. Control Lett. , vol.1 , pp. 288-294
    • Deng, J.L.1
  • 21
    • 0003376068 scopus 로고
    • A constrained unfolding methodology for product positioning
    • W.S. Desarbo, V.R. Rao A constrained unfolding methodology for product positioning Market. Sci. 5 1 1986 1 19
    • (1986) Market. Sci. , vol.5 , Issue.1 , pp. 1-19
    • Desarbo, W.S.1    Rao, V.R.2
  • 22
    • 84888869357 scopus 로고    scopus 로고
    • Recursive partitioning for missing data imputation in the presence of interaction effects
    • L.L. Doove, S.V. Buuren, E. Dusseldorp Recursive partitioning for missing data imputation in the presence of interaction effects Comput. Stat. Data Anal. 72 2013 92 104
    • (2013) Comput. Stat. Data Anal. , vol.72 , pp. 92-104
    • Doove, L.L.1    Buuren, S.V.2    Dusseldorp, E.3
  • 23
    • 84885094995 scopus 로고    scopus 로고
    • Partial imputation of unseen records to improve classification using a hybrid multi-layered artificial immune system and genetic algorithm
    • M. Duma, T. Marwala, B. Twala, F. Nelwamondo Partial imputation of unseen records to improve classification using a hybrid multi-layered artificial immune system and genetic algorithm Appl. Soft Comput. 13 2013 4461 4480
    • (2013) Appl. Soft Comput. , vol.13 , pp. 4461-4480
    • Duma, M.1    Marwala, T.2    Twala, B.3    Nelwamondo, F.4
  • 24
    • 0037005708 scopus 로고    scopus 로고
    • Estimation of missing stream flow data using the principles of chaos theory
    • A. Elshorbagy, S.P. Simonovic, U.S. Panu Estimation of missing stream flow data using the principles of chaos theory J. Hydrol. 255 1 2002 123 133
    • (2002) J. Hydrol. , vol.255 , Issue.1 , pp. 123-133
    • Elshorbagy, A.1    Simonovic, S.P.2    Panu, U.S.3
  • 25
    • 84890117828 scopus 로고    scopus 로고
    • Missing data in longitudinal studies: Cross-sectional multiple imputation provides similar estimates to full-information maximum likelihood
    • M.A. Ferro Missing data in longitudinal studies: cross-sectional multiple imputation provides similar estimates to full-information maximum likelihood Ann. Epidemiol. 24 2014 75 77
    • (2014) Ann. Epidemiol. , vol.24 , pp. 75-77
    • Ferro, M.A.1
  • 26
    • 38249042989 scopus 로고
    • A pragmatic view of accuracy measurement in forecasting
    • E. Flores A pragmatic view of accuracy measurement in forecasting Omega 14 2 1986 93 98
    • (1986) Omega , vol.14 , Issue.2 , pp. 93-98
    • Flores, E.1
  • 27
    • 0036732448 scopus 로고    scopus 로고
    • Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems
    • B. Gabrys Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems Int. J. Approx. Reason. 30 2002 149 179
    • (2002) Int. J. Approx. Reason. , vol.30 , pp. 149-179
    • Gabrys, B.1
  • 28
    • 79960233365 scopus 로고    scopus 로고
    • Missing data imputation in multivariate data by evolutionary algorithms
    • J.C.F. García, D. Kalenatic, C.A.L. Bello Missing data imputation in multivariate data by evolutionary algorithms Comput. Hum. Behav. 27 2011 1468 1474
    • (2011) Comput. Hum. Behav. , vol.27 , pp. 1468-1474
    • García, J.C.F.1    Kalenatic, D.2    Bello, C.A.L.3
  • 31
    • 84923608372 scopus 로고    scopus 로고
    • Data imputation via evolutionary computation, clustering and a neural network
    • C. Gautam, V. Ravi Data imputation via evolutionary computation, clustering and a neural network Neurocomputing 156 2015 134 142
    • (2015) Neurocomputing , vol.156 , pp. 134-142
    • Gautam, C.1    Ravi, V.2
  • 32
    • 84896500167 scopus 로고    scopus 로고
    • A practical comparison of single and multiple imputation methods to handle complex missing data in air quality datasets
    • M.P. Gómez-Carracedo, J.M. Andrade, P. López-Mahía, S. Muniategui, D. Prada A practical comparison of single and multiple imputation methods to handle complex missing data in air quality datasets Chemom. Intell. Lab. Syst. 134 2014 23 33
    • (2014) Chemom. Intell. Lab. Syst. , vol.134 , pp. 23-33
    • Gómez-Carracedo, M.P.1    Andrade, J.M.2    López-Mahía, P.3    Muniategui, S.4    Prada, D.5
  • 33
    • 0030085894 scopus 로고    scopus 로고
    • Estimating missing values using neural networks
    • A. Gupta, M.S. Lam Estimating missing values using neural networks J. Oper. Res. Soc. 47 2 1996 229 238
    • (1996) J. Oper. Res. Soc. , vol.47 , Issue.2 , pp. 229-238
    • Gupta, A.1    Lam, M.S.2
  • 34
    • 0023515080 scopus 로고
    • Counterpropagation networks
    • R. Hecht-Nielsen Counterpropagation networks Appl. Opt. 26 1987 4979 4984
    • (1987) Appl. Opt. , vol.26 , pp. 4979-4984
    • Hecht-Nielsen, R.1
  • 35
    • 33747356781 scopus 로고    scopus 로고
    • The problem of missing data in geoscience databases
    • S. Henley The problem of missing data in geoscience databases Comput. Geosci. 32 2006 1368 1377
    • (2006) Comput. Geosci. , vol.32 , pp. 1368-1377
    • Henley, S.1
  • 36
    • 84941584223 scopus 로고    scopus 로고
    • accessed 18.07.15
    • http://www.cis.hut.fi/projects/somtoolbox/, 2015 (accessed 18.07.15).
    • (2015)
  • 37
    • 84941584224 scopus 로고    scopus 로고
    • accessed 11.11.14
    • http://www.disat.unimib.it/chm, 2014 (accessed 11.11.14).
    • (2014)
  • 38
    • 84941584225 scopus 로고    scopus 로고
    • retrieved from, StatLib library, Carnegie Mellon University, (accessed 18.07.15)
    • E. Ramos, D. Donoho, Auto MPG dataset retrieved from http://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/auto-mpg.data, StatLib library, Carnegie Mellon University, 2015 (accessed 18.07.15).
    • (2015) Auto MPG Dataset
    • Ramos, E.1    Donoho, D.2
  • 39
    • 84941584226 scopus 로고    scopus 로고
    • retrieved from, (accessed 11.11.14)
    • P. Cortez, A. Morais, Forest Fire dataset retrieved from http://archive.ics.uci.edu/ml/machine-learning-databases/forest-fires/forestfires.csv, 2014 (accessed 11.11.14).
    • (2014) Forest Fire Dataset
    • Cortez, P.1    Morais, A.2
  • 40
    • 84997790444 scopus 로고    scopus 로고
    • retrieved from, (accessed 18.07.15)
    • D. Harrison, D.L. Rubinfeld, Boston Housing dataset retrieved from http://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data, 2015 (accessed 18.07.15).
    • (2015) Boston Housing Dataset
    • Harrison, D.1    Rubinfeld, D.L.2
  • 41
    • 84871982496 scopus 로고    scopus 로고
    • retrieved from, (accessed 18.07.15)
    • R.A. Fisher, Iris dataset retrieved from http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data, 2015 (accessed 18.07.15).
    • (2015) Iris Dataset
    • Fisher, R.A.1
  • 44
    • 84941570993 scopus 로고    scopus 로고
    • retrieved from, (accessed 18.07.15)
    • Wine dataset retrieved from http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data, 2015 (accessed 18.07.15).
    • (2015) Wine Dataset
  • 45
    • 84941584230 scopus 로고    scopus 로고
    • retrieved from, StatLib library, Carnegie Mellon University, (accessed 18.07.15)
    • R.W. Johnson, Bodyfat dataset retrieved from http://lib.stat.cmu.edu/datasets/bodyfat, StatLib library, Carnegie Mellon University, 2015 (accessed 18.07.15).
    • (2015) Bodyfat Dataset
    • Johnson, R.W.1
  • 46
    • 84941584231 scopus 로고    scopus 로고
    • retrieved from, (accessed 18.07.15)
    • Spanish dataset retrieved from http://www.tbb.org.tr/english/bulten/yillik/2000/ratios.xls, 2015 (accessed 18.07.15).
    • (2015) Spanish Dataset
  • 47
    • 84889688873 scopus 로고    scopus 로고
    • Incomplete-case nearest neighbor imputation in software measurement data
    • J.V. Hulse, T.M. Khoshgoftaar Incomplete-case nearest neighbor imputation in software measurement data Inform. Sci. 259 2014 596 610
    • (2014) Inform. Sci. , vol.259 , pp. 596-610
    • Hulse, J.V.1    Khoshgoftaar, T.M.2
  • 49
    • 84912002566 scopus 로고    scopus 로고
    • Imputation of missing data in time series for air pollutants
    • W.L. Junger, A.P. Leon Imputation of missing data in time series for air pollutants Atmos. Environ. 102 2015 96 104
    • (2015) Atmos. Environ. , vol.102 , pp. 96-104
    • Junger, W.L.1    Leon, A.P.2
  • 50
    • 84881242648 scopus 로고    scopus 로고
    • Locally linear reconstruction based missing value imputation for supervised learning
    • P. Kang Locally linear reconstruction based missing value imputation for supervised learning Neurocomputing 118 2013 65 78
    • (2013) Neurocomputing , vol.118 , pp. 65-78
    • Kang, P.1
  • 54
  • 56
    • 84885954235 scopus 로고    scopus 로고
    • Nearest neighbour imputation using spatial-temporal correlations in wireless sensor networks
    • Y.Y. Li, L.E. Parker Nearest neighbour imputation using spatial-temporal correlations in wireless sensor networks Informat. Fusion 15 2014 64 79
    • (2014) Informat. Fusion , vol.15 , pp. 64-79
    • Li, Y.Y.1    Parker, L.E.2
  • 57
    • 84865233213 scopus 로고    scopus 로고
    • Noisy data elimination using mutual k-nearest neighbor for classification mining
    • H. Liu, S. Zhang Noisy data elimination using mutual k-nearest neighbor for classification mining J. Syst. Softw. 85 5 2012 1067 1074
    • (2012) J. Syst. Softw. , vol.85 , Issue.5 , pp. 1067-1074
    • Liu, H.1    Zhang, S.2
  • 58
    • 19844365583 scopus 로고    scopus 로고
    • The auto-associative neural network in signal analysis II. Application to on-line monitoring of a simulated BWR component
    • M. Marseguerra, A. Zoia The auto-associative neural network in signal analysis II. Application to on-line monitoring of a simulated BWR component Ann. Nuclear Energy 32 11 2002 1207 1223
    • (2002) Ann. Nuclear Energy , vol.32 , Issue.11 , pp. 1207-1223
    • Marseguerra, M.1    Zoia, A.2
  • 59
    • 33644880300 scopus 로고    scopus 로고
    • Fault classification in structures with incomplete measured data using auto associative neural networks and genetic algorithm
    • T. Marwala, S. Chakraverty Fault classification in structures with incomplete measured data using auto associative neural networks and genetic algorithm Current Sci. India 90 4 2006 542 548
    • (2006) Current Sci. India , vol.90 , Issue.4 , pp. 542-548
    • Marwala, T.1    Chakraverty, S.2
  • 60
    • 79956146364 scopus 로고    scopus 로고
    • Natick, Massachusetts: The MathWorks Inc.
    • MATLAB version 7.10.0. Natick, Massachusetts: The MathWorks Inc., 2010.
    • (2010) MATLAB Version 7.10.0
  • 62
    • 77649236297 scopus 로고    scopus 로고
    • X-SOM and L-SOM: A double classification approach for missing value imputation
    • P. Merlin, A. Sorjamaa, B. Maillet, A. Lendasse X-SOM and L-SOM: a double classification approach for missing value imputation Neurocomputing 73 2010 1103 1108
    • (2010) Neurocomputing , vol.73 , pp. 1103-1108
    • Merlin, P.1    Sorjamaa, A.2    Maillet, B.3    Lendasse, A.4
  • 63
    • 84876958285 scopus 로고    scopus 로고
    • A dynamic programming approach to missing data estimation using neural networks
    • F.V. Nelwamondo, D. Golding, T. Marawala A dynamic programming approach to missing data estimation using neural networks Informat. Sci. 237 2013 49 58
    • (2013) Informat. Sci. , vol.237 , pp. 49-58
    • Nelwamondo, F.V.1    Golding, D.2    Marawala, T.3
  • 64
    • 84892169160 scopus 로고    scopus 로고
    • A computational intelligence based online data imputation method: An application for banking
    • K.J. Nishanth, V. Ravi A computational intelligence based online data imputation method: an application for banking J. Inform. Process. Syst. 9 4 2013 633 650
    • (2013) J. Inform. Process. Syst. , vol.9 , Issue.4 , pp. 633-650
    • Nishanth, K.J.1    Ravi, V.2
  • 65
    • 84861186486 scopus 로고    scopus 로고
    • Soft computing based imputation and hybrid data and text mining: The case of predicting the severity of phishing alerts
    • K.J. Nishanth, V. Ravi, N. Ankaiah, I. Bose Soft computing based imputation and hybrid data and text mining: the case of predicting the severity of phishing alerts Expert Syst. Appl. 39 12 2012 10583 10589
    • (2012) Expert Syst. Appl. , vol.39 , Issue.12 , pp. 10583-10589
    • Nishanth, K.J.1    Ravi, V.2    Ankaiah, N.3    Bose, I.4
  • 66
    • 80054087409 scopus 로고    scopus 로고
    • Filling of missing rainfall data in Luvuvhu river catchment using artificial neural networks
    • T.R. Nkuna, J.O. Odiyo Filling of missing rainfall data in Luvuvhu river catchment using artificial neural networks Phys. Chem. Earth A/B/C 36 14-15 2011 830 835
    • (2011) Phys. Chem. Earth A/B/C , vol.36 , Issue.14-15 , pp. 830-835
    • Nkuna, T.R.1    Odiyo, J.O.2
  • 67
    • 0043007739 scopus 로고    scopus 로고
    • Neural network imputation applied to the Norwegian 1990 population census data
    • S. Nordbotten Neural network imputation applied to the Norwegian 1990 population census data J. Off. Stat. 12 1996 385 401
    • (1996) J. Off. Stat. , vol.12 , pp. 385-401
    • Nordbotten, S.1
  • 68
    • 79951578021 scopus 로고    scopus 로고
    • Missing data analysis with fuzzy C-Means: A study of its application in a psychological scenario
    • G.D. Nuovo Missing data analysis with fuzzy C-Means: A study of its application in a psychological scenario Expert Syst. Appl. 38 6 2011 6793 6797
    • (2011) Expert Syst. Appl. , vol.38 , Issue.6 , pp. 6793-6797
    • Nuovo, G.D.1
  • 69
    • 0004401956 scopus 로고    scopus 로고
    • Hybrid classifiers for financial multicriteria decision making: The case of bankruptcy prediction
    • I. Olmeda, E. Fernandez Hybrid classifiers for financial multicriteria decision making: the case of bankruptcy prediction Comput. Econom. 10 1997 317 335
    • (1997) Comput. Econom. , vol.10 , pp. 317-335
    • Olmeda, I.1    Fernandez, E.2
  • 70
    • 84920903639 scopus 로고    scopus 로고
    • A kernel-assisted imputation estimating method for the additive hazards model with missing censoring indicator
    • Z. Qiu, X. Chen, Y. Zhou A kernel-assisted imputation estimating method for the additive hazards model with missing censoring indicator Stat. Probab. Lett. 98 2015 89 97
    • (2015) Stat. Probab. Lett. , vol.98 , pp. 89-97
    • Qiu, Z.1    Chen, X.2    Zhou, Y.3
  • 71
    • 0343526733 scopus 로고    scopus 로고
    • MVC - A preprocessing method to deal with missing values
    • A. Ragel, B. Cremilleux MVC - a preprocessing method to deal with missing values Knowl. Based Syst. 12 1999 285 291
    • (1999) Knowl. Based Syst. , vol.12 , pp. 285-291
    • Ragel, A.1    Cremilleux, B.2
  • 72
    • 84885426937 scopus 로고    scopus 로고
    • Missing value imputation using decision trees and decision forests by splitting and merging records: Two novel techniques
    • Md.G. Rahman, Md.Z. Islam Missing value imputation using decision trees and decision forests by splitting and merging records: two novel techniques Knowl. Based Syst. 53 2013 51 65
    • (2013) Knowl. Based Syst. , vol.53 , pp. 51-65
    • Rahman, Md.G.1    Islam, Md.Z.2
  • 73
    • 0037470203 scopus 로고    scopus 로고
    • Separation of data on the training and test set for modelling: A case study for modelling of five colour properties of a white pigment
    • K. Rajer-Kanduč, J. Zupan, N. Majcen Separation of data on the training and test set for modelling: a case study for modelling of five colour properties of a white pigment Chemom. Intell. Lab. Syst. 65 2003 221 229
    • (2003) Chemom. Intell. Lab. Syst. , vol.65 , pp. 221-229
    • Rajer-Kanduč, K.1    Zupan, J.2    Majcen, N.3
  • 75
    • 84976616101 scopus 로고    scopus 로고
    • Missing data: Weighting and imputation
    • Elsevier
    • P.J. Rathouz Missing data: weighting and imputation Encyclopaedia of Health Economics 2014 Elsevier 292 298
    • (2014) Encyclopaedia of Health Economics , pp. 292-298
    • Rathouz, P.J.1
  • 76
    • 84899895795 scopus 로고    scopus 로고
    • A new online data imputation method based on general regression auto associative neural network
    • V. Ravi, M. Krishna A new online data imputation method based on general regression auto associative neural network Neurocomputing 138 2014 207 212
    • (2014) Neurocomputing , vol.138 , pp. 207-212
    • Ravi, V.1    Krishna, M.2
  • 77
    • 0002081757 scopus 로고
    • Self-organization with partial data network
    • T. Samad, S.A. Harp Self-organization with partial data network Comput. Neural Syst. 3 1992 205 212
    • (1992) Comput. Neural Syst. , vol.3 , pp. 205-212
    • Samad, T.1    Harp, S.A.2
  • 79
    • 0035880503 scopus 로고    scopus 로고
    • Singular spectrum analysis for time series with missing data
    • D.H. Schoellhamer Singular spectrum analysis for time series with missing data Geophys. Res. Lett. 28 16 2001 3187 3190
    • (2001) Geophys. Res. Lett. , vol.28 , Issue.16 , pp. 3187-3190
    • Schoellhamer, D.H.1
  • 80
    • 0002812717 scopus 로고
    • Dealing with missing values in neural network based diagnostic systems
    • P.K. Sharpe, R.J. Solly Dealing with missing values in neural network based diagnostic systems Neural Comput. Appl. 3 2 1995 73 77
    • (1995) Neural Comput. Appl. , vol.3 , Issue.2 , pp. 73-77
    • Sharpe, P.K.1    Solly, R.J.2
  • 83
    • 84920696294 scopus 로고    scopus 로고
    • Single imputation with multilayer perceptron and multiple imputation combining multilayer perceptron and k-nearest neighbours for monotone patterns
    • E. Silva-Ramírez, R. Pino-Mejías, M. López-Coello Single imputation with multilayer perceptron and multiple imputation combining multilayer perceptron and k-nearest neighbours for monotone patterns Appl. Soft Comput. 29 2015 65 74
    • (2015) Appl. Soft Comput. , vol.29 , pp. 65-74
    • Silva-Ramírez, E.1    Pino-Mejías, R.2    López-Coello, M.3
  • 84
    • 33750994891 scopus 로고    scopus 로고
    • A new imputation method for small software project data sets
    • Q. Song, M. Shepperd A new imputation method for small software project data sets J. Syst. Software 80 1 2007 51 62
    • (2007) J. Syst. Software , vol.80 , Issue.1 , pp. 51-62
    • Song, Q.1    Shepperd, M.2
  • 85
    • 84912055274 scopus 로고    scopus 로고
    • A hybrid approach to integrate fuzzy C-means based imputation method with genetic algorithm for missing traffic volume data estimation
    • J. Tang, G. Zhang, Y. Wang, H. Wang, F. Liu A hybrid approach to integrate fuzzy C-means based imputation method with genetic algorithm for missing traffic volume data estimation Transp. Res. Part C: Emerg. Technol. 51 2015 29 40
    • (2015) Transp. Res. Part C: Emerg. Technol. , vol.51 , pp. 29-40
    • Tang, J.1    Zhang, G.2    Wang, Y.3    Wang, H.4    Liu, F.5
  • 87
    • 84894565892 scopus 로고    scopus 로고
    • "Missing data analyses: A hybrid multiple imputation algorithm using grey system theory and entropy based on clustering
    • J. Tian, B. Yu, D. Yu, S. Ma "Missing data analyses: a hybrid multiple imputation algorithm using grey system theory and entropy based on clustering Appl. Intell. 40 2013 1 13
    • (2013) Appl. Intell. , vol.40 , pp. 1-13
    • Tian, J.1    Yu, B.2    Yu, D.3    Ma, S.4
  • 89
    • 0036126816 scopus 로고    scopus 로고
    • Attrition in longitudinal studies: How to deal with missing data
    • J. Twisk, W.D. Vente Attrition in longitudinal studies: How to deal with missing data J. Clinical Epidemiol. 55 2002 329 337
    • (2002) J. Clinical Epidemiol. , vol.55 , pp. 329-337
    • Twisk, J.1    Vente, W.D.2
  • 90
    • 38049168357 scopus 로고    scopus 로고
    • SOM-based data visualization methods
    • J. Vesanto SOM-based data visualization methods Intell. Data Anal. 3 1999 111 126
    • (1999) Intell. Data Anal. , vol.3 , pp. 111-126
    • Vesanto, J.1
  • 92
    • 0001884644 scopus 로고
    • Individual comparisons by ranking methods
    • F. Wilcoxon Individual comparisons by ranking methods Biometrics Bull 1 1945 80 83
    • (1945) Biometrics Bull , vol.1 , pp. 80-83
    • Wilcoxon, F.1
  • 93
    • 84941584234 scopus 로고    scopus 로고
    • Retrieved from, (accessed 18.07.15)
    • Retrieved from www.sussex.ac.uk/Users/grahamh/RM1web/WilcoxonTable2005.pdf, 2015 (accessed 18.07.15).
    • (2015)
  • 94
    • 0033350105 scopus 로고    scopus 로고
    • Training algorithm with incomplete data for feed-forward neural networks
    • S.Y. Yoon, S.Y. Lee Training algorithm with incomplete data for feed-forward neural networks Neural Process. Lett. 10 1999 171 179
    • (1999) Neural Process. Lett. , vol.10 , pp. 171-179
    • Yoon, S.Y.1    Lee, S.Y.2
  • 95
    • 84865249371 scopus 로고    scopus 로고
    • Nearest neighbor selection for iteratively kNN imputation
    • S. Zhang Nearest neighbor selection for iteratively kNN imputation J. Syst. Softw. 85 11 2012 2541 2552
    • (2012) J. Syst. Softw. , vol.85 , Issue.11 , pp. 2541-2552
    • Zhang, S.1
  • 96
    • 0030737774 scopus 로고    scopus 로고
    • Kohonen and counterpropagation artificial neural networks in analytical chemistry
    • J. Zupan, M. Novic, I. Ruisánchez Kohonen and counterpropagation artificial neural networks in analytical chemistry Chemom. Intell. Lab. Syst. 38 1997 1 23
    • (1997) Chemom. Intell. Lab. Syst. , vol.38 , pp. 1-23
    • Zupan, J.1    Novic, M.2    Ruisánchez, I.3
  • 97
    • 0028864978 scopus 로고
    • Neural networks with counter-propagation learning strategy used for modelling
    • J. Zupan, M. Novic, J. Gasteiger Neural networks with counter-propagation learning strategy used for modelling Chemom. Intell. Lab. Syst 27 1995 175 187
    • (1995) Chemom. Intell. Lab. Syst , vol.27 , pp. 175-187
    • Zupan, J.1    Novic, M.2    Gasteiger, J.3


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