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Filter versus wrapper gene selection approaches in DNA microarray domains
TLDR
The application of a gene selection process is proposed, which also enables the biology researcher to focus on promising gene candidates that actively contribute to classification in these large scale microarrays, by an extensive comparison with more popular filter techniques. Expand
Learning Bayesian networks in the space of structures by estimation of distribution algorithms
TLDR
Two novel population‐based stochastic search approaches, univariate marginal distribution algorithm (UMDA) and population-based incremental learning (PBIL) are used to learn a Bayesian network structure from a database of cases in a score + search framework. Expand
A review of estimation of distribution algorithms in bioinformatics
TLDR
A basic taxonomy of EDA techniques is set out, underlining the nature and complexity of the probabilistic model of each EDA variant, and emphasizing the EDA paradigm's potential for further research in this domain. Expand
Gene Selection For Cancer Classification Using Wrapper Approaches
TLDR
Stating the optimal selection of genes as a search task, an automatic and robust choice in the genes finally selected is performed, in contrast to previous works that research the same types of problems. Expand
Gene selection by sequential search wrapper approaches in microarray cancer class prediction
TLDR
By the use of the gene selection procedure, the accuracy of supervised algorithms is significantly improved and the number of genes of the classification models is notably reduced for all datasets. Expand
Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS
The transjugular intrahepatic portosystemic shunt (TIPS) is a treatment for cirrhotic patients with portal hypertension. A subgroup of patients dies in the first 6 months and another subgroup lives aExpand
An Empirical Comparison of Discrete Estimation of Distribution Algorithms
TLDR
An empirical comparison between different im-plementations of Estimation of Distribution Algorithms in discrete domains with three different criteria: the convergence velocity, the convergence reliability and the scalability is presented. Expand
Microarray Data Analysis and Management in Colorectal Cancer
TLDR
The analysis of microarrays data using colon cancer samples is presented in order to determine the differentially expressed genes underlying this disease process and permits the location of most prevalent processes that are altered during under this disease. Expand
Learning Bayesian Networks by Floating Search Methods
TLDR
The presented sequential search methods are an adaptation of a pair of algorithms proposed to feature subset selection: Sequential Forward Floating Selection and Sequential Backward Floating Selection that show promising results for the floating approach to the learning Bayesian network problem. Expand
Selective Classifiers Can Be Too Restrictive: A Case-Study in Oesophageal Cancer
TLDR
It is argued that especially the wrapper approach to feature selection may result in classifiers that are too selective for such a setting and that, in fact, some redundancy is required to arrive at a reasonable classification accuracy in practice. Expand
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