Hybrid Classifiers - Methods of Data, Knowledge, and Classifier Combination (Paperback, Softcover reprint of the original 1st ed. 2014)

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.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Studies in Computational Intelligence, 519
Release date:	September 2016
First published:	2014
Authors:	Michal Wozniak
Dimensions:	235 x 155 x 13mm (L x W x T)
Format:	Paperback
Pages:	217
Edition:	Softcover reprint of the original 1st ed. 2014
ISBN-13:	978-3-662-52304-9
Categories:	Books > Computing & IT > General
LSN:	3-662-52304-3
Barcode:	9783662523049

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