methods of data, knowledge, and classifier combination /
First Statement of Responsibility
Michał Woźniak
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xvi, 217 pages) :
Other Physical Details
illustrations
SERIES
Series Title
Studies in Computational Intelligence,
Volume Designation
v.519
ISSN of Series
1860-949X ;
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index
CONTENTS NOTE
Text of Note
Data and knowledge hybridization -- Classifier hybridization -- Chosen applications of hybrid classifiers -- Conclusions
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SUMMARY OR ABSTRACT
Text of Note
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