Unsupervised Learning Of Bayesian Networks Via Estimation Of Distribution Algorithms: An Application To Gene Expression Data Clustering
暂无分享,去创建一个
[1] Pedro Larrañaga,et al. An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering , 2000, Pattern Recognit. Lett..
[2] Nir Friedman,et al. Class discovery in gene expression data , 2001, RECOMB.
[3] Thomas Bäck,et al. Evolutionary Algorithms in Theory and Practice , 1996 .
[4] Pedro Larrañaga,et al. Learning Bayesian networks in the space of structures by estimation of distribution algorithms , 2003, Int. J. Intell. Syst..
[5] David E. Goldberg,et al. A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..
[6] Heinz Mühlenbein,et al. The Equation for Response to Selection and Its Use for Prediction , 1997, Evolutionary Computation.
[7] Martin Beibel. Selection of Informative Genes in Gene Expression Based Diagnosis: A Nonparametric Approach , 2000, ISMDA.
[8] Nir Friedman,et al. The Bayesian Structural EM Algorithm , 1998, UAI.
[9] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .
[10] Enrique F. Castillo,et al. Expert Systems and Probabilistic Network Models , 1996, Monographs in Computer Science.
[11] David Maxwell Chickering,et al. Learning Bayesian Networks is NP-Complete , 2016, AISTATS.
[12] David W. Aha,et al. Instance-Based Learning Algorithms , 1991, Machine Learning.
[13] Pedro Larrañaga,et al. Learning Bayesian networks for clustering by means of constructive induction , 1999, Pattern Recognit. Lett..
[14] J. A. Lozano,et al. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .
[15] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[16] Ivan Bratko,et al. On Estimating Probabilities in Tree Pruning , 1991, EWSL.
[17] Finn V. Jensen,et al. Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.
[18] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[19] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[20] Michal Linial,et al. Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..
[21] Ron Kohavi,et al. Wrappers for Feature Subset Selection , 1997, Artif. Intell..
[22] Thomas Bäck,et al. Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .
[23] J. Mesirov,et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.
[24] Pedro Larrañaga,et al. Estimation of Distribution Algorithms , 2002, Genetic Algorithms and Evolutionary Computation.
[25] H. Mühlenbein,et al. From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.
[26] Bojan Cestnik,et al. Estimating Probabilities: A Crucial Task in Machine Learning , 1990, ECAI.
[27] G. McLachlan,et al. The EM algorithm and extensions , 1996 .
[28] José Manuel Gutiérrez,et al. Expert Systems and Probabiistic Network Models , 1996 .
[29] Pedro Larrañaga,et al. Filter versus wrapper gene selection approaches in DNA microarray domains , 2004, Artif. Intell. Medicine.
[30] Pedro Larrañaga,et al. Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction , 2002, Machine Learning.
[31] Judea Pearl,et al. Probabilistic reasoning in intelligent systems , 1988 .
[32] David Maxwell Chickering,et al. Learning Equivalence Classes of Bayesian Network Structures , 1996, UAI.
[33] Daniel Kahneman,et al. Probabilistic reasoning , 1993 .
[34] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[35] David Maxwell Chickering,et al. Learning Bayesian Networks: The Combination of Knowledge and Statistical Data , 1994, Machine Learning.