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Hybrid Classifiers: Methods of Data, Knowledge, and Classifier Combination: 519 (Studies in Computational Intelligence) - Tapa blanda
Sinopsis
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.
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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.
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Hybrid Classifiers: Methods of Data, Knowledge, and Classifier Combination (Studies in Computational Intelligence, 519)
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Hybrid Classifiers: Methods of Data, Knowledge, and Classifier Combination (Studies in Computational Intelligence, 519)
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Hybrid Classifiers
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ISBN 13: 9783662523049
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 236 pp. Englisch. Nº de ref. del artículo: 9783662523049
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Hybrid Classifiers
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ISBN 10: 3662523043
ISBN 13: 9783662523049
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Latest research on Classifier FusionPresents Methods of Data and Classifier FusionWritten by leading experts in the fieldThis book delivers a definite and compact knowledge on how hybridization can help improving the quality of c. Nº de ref. del artículo: 449138612
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Hybrid Classifiers : Methods of Data, Knowledge, and Classifier Combination
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Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 27440710
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Hybrid Classifiers
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Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 2016, 2016
ISBN 10: 3662523043
ISBN 13: 9783662523049
Nuevo
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Taschenbuch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 236 pp. Englisch. Nº de ref. del artículo: 9783662523049
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