AN ANALYSIS OF FEATURE SELECTION TECHNIQUES FOR AN EVOLUTIONARY APPROACH TO GENETIC ALGORITHMS

Abstract

Data magnitude is growing expeditiously, which pretends the challenges to extensive majority of current mining and learning algorithms, such as the bane of dimensionality, huge storage requirement, and enormous computational cost. Feature selection has been proven to be an effective and efcient way to prepare high-dimensional data for data mining and machine learning. The recent evolution of novel techniques and new types of data and aspects not only advances existing feature selection research but also emerges the feature selection constantly, becoming applicable to a expansive range of applications. In this entry, we aim to provide a basic introduction to feature selection including basic concepts, classications of existing systems, recent development, and applications.