Matlab toolbox for Estimation of Distribution Algorithms (MATEDA-2.0) The package allows the optimization of single and multi-objective problems with estimation of distribution algorithms (EDAs) based on undirected graphical models and Bayesian networks. The implementation is conceived for allowing the incorporation by the user of different combinations of selection, learning, sampling, and local search procedures. Other included methods allow the analysis of the structures learned by the probabilistic models, the visualization of particular features of these structures and the use of the probabilistic models as fitness modeling tools.
Keywords for this software
References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Ceberio, Josu; Irurozki, Ekhine; Mendiburu, Alexander; Lozano, Jose A.: A review of distances for the Mallows and generalized Mallows estimation of distribution algorithms (2015)
- Santana, Roberto; Bielza, Concha; Larrañaga, Pedro: Regularized logistic regression and multiobjective variable selection for classifying MEG data (2012)