Feature Selection in Data Mining: Approaches Based on Information Theory - Softcover

Zhou, Jing

Softcover

ISBN 10: 3836427117 ISBN 13: 9783836427111

Verlag: VDM Verlag Dr. Müller, 2007

Inhaltsangabe

In many predictive modeling tasks, one has a fixed set of observations from which a vast, or even infinite, set of potentially predictive features can be computed. Of these features, often only a small number are expected to be useful in a predictive model. Models which use the entire set of features will almost certainly overfit on future data sets. The book presents streamwise feature selection which interleaves the process of generating new features with that of feature testing. Streamwise feature selection scales well to large feature sets. The book also describes how to use streamwise feature seleciton in multivariate regressions. It includes a review of traditional feature selecitions in a general framework based on information theory, and compares these methods with streamwise feature selection on various real and synthetic data sets. This book is intended to be used by researchers in machine learning, data mining, and knowledge discovery.

Details zur Ausgabe

• Verlag: VDM Verlag Dr. Müller
• Erscheinungsdatum: 2007
• Sprache: Englisch
• ISBN 10: 3836427117
• ISBN 13: 9783836427111
• Einband: Taschenbuch
• Auflage: 1
• Anzahl der Seiten: 104
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Zeitfracht Medien GmbH; info-medien@zeitfracht.de; ; Ferdinand-Jühlke-Straße 7; Erfurt; 99095; Deutschland