Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

The paper summarizes the different characteristics of Web data, the basic components of
Web mining and its different types, and the current state of the art. The reason for …

This paper proposes a novel hybrid genetic algorithm for feature selection. Local search
operations are devised and embedded in hybrid GAs to fine-tune the search. The operations …

Newly developed Web-based educational technologies offer researchers unique
opportunities to study how students learn and what approaches to learning lead to success …

Feature selection (FS) was regarded as a global combinatorial optimization problem. FS is
used to simplify and enhance the quality of high-dimensional datasets by selecting …

This chapter discusses the use of evolutionary algorithms, particularly genetic algorithms
and genetic programming, in data mining and knowledge discovery. We focus on the data …

The feature selection process constitutes a commonly encountered problem of global
combinatorial optimization. This process reduces the number of features by removing …

Names: Gupta, Brij, 1982-editor.| Sheng, Quan Z. editor. Title: Machine learning for computer
and cyber security: principles, algorithms, and practices/editors Brij B. Gupta, National …

This paper presents an approach for classifying students in order to predict their final grade
based on features extracted from logged data in an education web-based system. A …

Real life data sets are often interspersed with noise, making the subsequent data mining
process difficult. The task of the classifier could be simplified by eliminating attributes that …