Hybrid Classifiers : Methods of Data, Knowledge, and Classifier Combination

Michal Wozniak

ISBN 10: 3642409962 / ISBN 13: 9783642409967

Published by Springer Berlin Heidelberg, 2013

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

Seller Inventory # 9783642409967

Bibliographic Details

• Title: Hybrid Classifiers : Methods of Data, Knowledge, and Classifier Combination
• Publisher: Springer Berlin Heidelberg
• Publication Date: 2013
• Language: English
• ISBN 10: 3642409962
• ISBN 13: 9783642409967
• Binding: Buch
• Condition: Neu

About this title

Synopsis

This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.