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Abstract
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762/5000
Feature Selection is one of the most important issues in the area of ??data classification. The purpose of the feature selection is to find the subset of the effective features of the primary data set, which increases the efficiency and reduces the cost of the data classification. In recent years, with the emergence of high-dimensional data sets and low sample sizes, there is a pressing need for effective methods of selecting effective features. In this paper, a cover method is proposed using evolutionary methods to select an effective feature in the data set.
The proposed algorithm has been used for the selection of the ARO evolutionary algorithm. Also, in this algorithm, to evaluate the suitability of each subset, a multi-layered neural network class is used. The proposed method is evaluated with two sets of data, in the field of image processing, signal processing of the brain.
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