… accurate than C4.5. In this paper we address the problem of feature subset selection using
two genetic-based search … when the features are selected randomly from the complete set of …

… The fitness function used for the genetic search process is … is set from 20, 30, 40 and 50,
and the crossover rate is set from … accuracy than performing instance selection first and feature …

… One approach to stereo matching is to use different local features to find correspondences.
The selection of an optimum feature set is the content of this paper. An operational software …

… three data sets and three existing feature selection methods. … to find subsets of features with
higher classification accuracy … data sets above, we find out that the rankings of features are …

… genetic search-based strategy. In our new version considered in this paper no full feature
sets … average ensemble accuracy on the test and validation sets for the four search strategies …

… In this paper, we present a genetic algorithm (GA) approach for searching for an appropriate
… Varying the feature subsets to create a diverse set of accurate predictors is the focus of this …

… FR measures feature-class relevance, then ranks features by … find a set of features that
performs well. It integrates the metrics for measuring feature-class relevance and feature–feature …

… In this study, a hybrid genetic algorithm is adopted to find a subset of features … feature
selection and excellent classification accuracy of the method on a range of benchmark data sets…

… the crossover operator of genetic algorithms, the strong local search ability of greedy …
features and tested on a hold-out set, and prediction accuracy is used to determine the feature set …

… the genetic search… accuracy of classification on the selected feature sets for all the datasets,
compared with the baseline KNN on the full features; for German credit dataset, the accuracy …