Performance Evaluation of Genetic Algorithm Selection Methods in Outlier Detection: Further Analysis

Ayodeji Oyeyinka EFUNBOADE, &
Feature selection is very crucial in the activities of soft computing algorithms for quality, precision and accuracy. This paper evaluates the performance of some feature selection methods of Genetic Algorithm in outlier detection on fingerprint images. Roulette wheel, Rank and Tournament methods were considered for feature selection and selected features were enhanced using h istogram equalization. K - nearest neighbor algorithm was employed for classification to detect outliers. The implementation of the experiment was carried...
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