This paper analyzes the performance of a genetic algorithm that utilizes tournament selection, one-point crossover, and a reordering operator. A model is proposed to describe the c...
In rough set theory, the problem of feature selection aims to retain the discriminatory power of original features. Many feature selection algorithms have been proposed, however, q...
Feature selection is a data preprocessing step for classi cation and data mining tasks. Traditionally, feature selection is done by selecting a minimum number of features that det...
We discuss the use of normal distribution theory as a tool to model the convergence characteristics of di erent GA selection schemes. The models predict the proportion of optimal a...
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...