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Results: 1-12 |
Results: 12
Feature subset selection by genetic algorithms and estimation of distribution algorithms - A case study in the survival of cirrhotic patients treatedwith TIPS
Authors: Inza, I Merino, M Larranaga, P Quiroga, J Sierra, B Girala, M
Citation: I. Inza et al., Feature subset selection by genetic algorithms and estimation of distribution algorithms - A case study in the survival of cirrhotic patients treatedwith TIPS, ARTIF INT M, 23(2), 2001, pp. 187-205
Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data
Authors: Sierra, B Serrano, N Larranaga, P Plasencia, EJ Inza, I Jimenez, JJ Revuelta, P Mora, ML
Citation: B. Sierra et al., Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data, ARTIF INT M, 22(3), 2001, pp. 233-248
Performance evaluation of compromise conditional Gaussian networks for data clustering
Authors: Pena, JM Lozano, JA Larranaga, P
Citation: Jm. Pena et al., Performance evaluation of compromise conditional Gaussian networks for data clustering, INT J APPRO, 28(1), 2001, pp. 23-50
Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms
Authors: Inza, I Larranaga, P Sierra, B
Citation: I. Inza et al., Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms, INT J APPRO, 27(2), 2001, pp. 143-164
Dimensionality reduction in unsupervised learning of conditional Gaussian networks
Authors: Pena, JM Lozano, JA Larranaga, P Inza, I
Citation: Jm. Pena et al., Dimensionality reduction in unsupervised learning of conditional Gaussian networks, IEEE PATT A, 23(6), 2001, pp. 590-603
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering
Authors: Pena, JM Lozano, JA Larranaga, P
Citation: Jm. Pena et al., An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering, PATT REC L, 21(8), 2000, pp. 779-786
Feature Subset Selection by Bayesian network-based optimization
Authors: Inza, I Larranaga, P Etxeberria, R Sierra, B
Citation: I. Inza et al., Feature Subset Selection by Bayesian network-based optimization, ARTIF INTEL, 123(1-2), 2000, pp. 157-184
Genetic algorithms: bridging the convergence gap
Authors: Lozano, JA Larranaga, P Grana, M Albizuri, FX
Citation: Ja. Lozano et al., Genetic algorithms: bridging the convergence gap, THEOR COMP, 229(1-2), 1999, pp. 11-22
Genetic algorithms for the travelling salesman problem: A review of representations and operators
Authors: Larranaga, P Kuijpers, CMH Murga, RH Inza, I Dizdarevic, S
Citation: P. Larranaga et al., Genetic algorithms for the travelling salesman problem: A review of representations and operators, ARTIF INT R, 13(2), 1999, pp. 129-170
Representing the behaviour of supervised classification learning algorithms by Bayesian networks
Authors: Inza, I Larranaga, P Sierra, B Etxeberria, R Lozano, J Pena, JM
Citation: I. Inza et al., Representing the behaviour of supervised classification learning algorithms by Bayesian networks, PATT REC L, 20(11-13), 1999, pp. 1201-1209
Learning Bayesian networks for clustering by means of constructive induction
Authors: Pena, JM Lozano, JA Larranaga, P
Citation: Jm. Pena et al., Learning Bayesian networks for clustering by means of constructive induction, PATT REC L, 20(11-13), 1999, pp. 1219-1230
An empirical comparison of four initialization methods for the K-Means algorithm
Authors: Pena, JM Lozano, JA Larranaga, P
Citation: Jm. Pena et al., An empirical comparison of four initialization methods for the K-Means algorithm, PATT REC L, 20(10), 1999, pp. 1027-1040
Risultati: 1-12 |