This book addresses the integration of two areas of computer science, namely data mining
and evolutionary algorithms. Both these areas have become increas ingly popular in the last …

Rapid developments in the field of genetic algorithms along with the popularity of the first
edition precipitated this completely revised, thoroughly updated second edition of The …

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 …

Computer-aided drug design has advanced rapidly in recent years, and multiple instances
of in silico designed molecules advancing to the clinic have demonstrated the contribution of …

Feature selection for data mining optimization receives quite a high demand especially on
high-dimensional feature vectors of a data. Feature selection is a method used to select the …

A genetic algorithm is used to build user profiles from a collection of documents previously
retrieved by the user. A fuzzy classification and a genetic term selection process provide a …

Cervical cancer is one of the most common cancers, accounting for 6% of all malignancies
in women (National Cancer Institute, 1999). The standard screening test for cervical cancer …

Feature subset selection is an important preprocessing task for pattern recognition, machine
learning or data mining applications. A Genetic Algorithm (GA) with a fuzzy fitness function …

Abstract Malignancy Associated Changes are subtle alterations in the morphology and
nuclear texture of cells in the vicinity of a malignant lesion. The phenomenon was first …

An improvement in the effectiveness of information retrieval by using genetic algorithms
(GAs) and fuzzy logic is demonstrated. A new classification of information retrieval models …