Now showing items 1-10 of 40
Using network mesures to test evolved NK-landscapes
In this paper we empirically investigate which are the structural characteristics that can help to predict the complexity of NK-landscape instances for estimation of distribution algorithms. To this end, we evolve instances ...
Learning Bayesian network classifiers for multidimensional supervised classification problems by means of a multiobjective approach
A classical supervised classification task tries to predict a single class variable based on a data set composed of a set of labeled examples. However, in many real domains more than one variable could be considered as a ...
MATEDA: A suite of EDA programs in Matlab
This paper describes MATEDA-2.0, a suite of programs in Matlab for estimation of distribution algorithms. The package allows the optimization of single and multi-objective problems with estimation of distribution algorithms ...
A quantitative analysis of estimation of distribution algorithms based on Bayesian networks
The successful application of estimation of distribution algorithms (EDAs) to solve different kinds of problems has reinforced their candidature as promising black-box optimization tools. However, their internal behavior is ...
A sensitivity study of bias and variance of k-fold cross-validation in prediction error estimation
In the machine learning field the performance of a classifier is usually measured in terms of prediction error. In most real-world problems, the error cannot be exactly calculated and it must be estimated. Therefore, it’s ...
On the application of estimation of distribution algorithms to multi-marker tagging SNP selection
This paper presents an algorithm for the automatic selection of a minimal subset of tagging single nucleotide polymorphisms (SNPs) using an estimation of distribution algorithm (EDA). The EDA stochastically searches the ...
A Preprocessing Procedure for Haplotype Inference by Pure Parsimony
Haplotype data is especially important in the study of complex diseases since it contains more information than genotype data. However, obtaining haplotype data is technically difficult and expensive. Computational methods ...
KAF: Kyoto Annotation Framework
This document presents the current draft of KAF: Kyoto Annotation Framework to be used within the KYOTO project. KAF aims to provide a reference format for the representation of semantic annotations.
Ontologies for representation of folk song metadata
The digital management of collections in museums, archives, libraries and galleries is an increasingly important part of cultural heritage studies. This paper describes a representation for folk song metadata, based on the ...
Learning Probability Distributions over Permutations by Means of Fourier Coefficients
A large and increasing number of data mining domains consider data that can be represented as permutations. Therefore, it is important to devise new methods to learn predictive models over datasets of permutations. However, ...