Computational Methods of Feature Selection

Highlighting current research issues, this clear, concise, and coherent volume introduces the basic concepts and principles, state-of-the-art algorithms, and inventive applications of feature selection. With excellent surveys, practical guidance, and comprehensive tutorials from leading experts, it chronicles the novel developments of feature selection that have emerged in recent years, including causal feature selection and Relief. The book also presents the latest methodologies and algorithms, such as the Las Vegas, Monte Carlo, and Bayes risk-weighted vector quantization algorithms, and contains real-world case studies from a variety of areas, including text classification, web mining, and bioinformatics.