… solving the feature selection problem. The subsets of variables selected by genetic algorithms
are generally more efficient than those obtained by classical methods of feature selection, …

… application of Genetic Algorithm (GA) for feature selection. … ) features were extracted from
set of images found in the Flavia dataset (a publicly available dataset). The extracted features …

… , experimental results show that the GAselected set of features leads to a higher recognition
… Genetic Algorithms in very large-scale feature selection (where the number of features is …

… a novel hybrid genetic algorithm for feature selection. Local … of feature selection algorithms,
the genetic algorithm (GA) is a … Furthermore, GA is naturally applicable to feature selection …

… wrapper, feedback, feature selection model is directly related to … the feature selection issue,
based upon the genetic algorithm … to fitness evaluation for genetic feature selection, based on …

… Genetic algorithms (GAs) can be very easily applied to feature selection ; in this paper it will
… In a GA applied to feature selection, the structure of the chromosomes is very simple, since …

In this paper, we review the feature selection problem in mining issues. The application of
soft computing techniques to data mining and knowledge discovery is now emerging in order …

… We refer to a as a feature selection vector and ~ti is a feature selection variable. Thus the
search space for the … Based on these properties of the score function (3.3) we anticipated …

… on the features chosen to represent the sequences. Results: In this paper, a feature selection
… If there is a continuous or smooth map from feature space to the classification target values, …

… approach that combines feature selection and data classi cation using Genetic Algorithms. …
searching for an optimal feature weighting, essentially warping the feature space to coalesce …