… exploration and application of Genetic Algorithm (GA) for feature selection. Particularly a binary
… In this work, hundred (100) features were extracted from set of images found in the Flavia …

… Genetic algorithms (GAs) can be very easily applied to feature selection ; in this paper it will
be shown that very good results are obtained with a `tailor made' configuration, in which the …

… 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 …

… set of features leads to a higher recognition rate than the original set does. Finally, Moser …
Genetic Algorithms in very large-scale feature selection (where the number of features is larger …

… This paper presents a genetic algorithm for feature selection which improves previous … ure
for genetic-based feature selection and: (i) is independent from a specific learning algorithm; (ii…

… the randomness of selection operation. Therefore, we propose a new … genetic algorithm,
as well as a fast version of rival genetic algorithm, to enhance the performance of GA in feature …

… This paper presents a new hybrid genetic algorithm (HGA) for feature selection (FS), called
as HGAFS. The vital aspect of this algorithm is the selection of salient feature subset within a …

… feature selection and data classi cation using Genetic Algo… Algorithms combined with a
K-nearest neighbor algorithm to … optimal feature weighting, essentially warping the feature space …

… genetic algorithm is adopted to find a subset of features that … search for the best subset of
features in a wrapper way, in … fitness function for the genetic algorithm. The inner optimization …

… In this paper we use a genetic algorithm (GA) for feature selection problem. The method
explores the space of possible subsets to obtain the set of features that maximizes the predictive …