Semi-Supervised and Unsupervised Machine Learning

Novel Strategies

Nonfiction, Science & Nature, Technology, Electronics
Cover of the book Semi-Supervised and Unsupervised Machine Learning by Amparo Albalate, Wolfgang Minker, Wiley
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Author: Amparo Albalate, Wolfgang Minker ISBN: 9781118586136
Publisher: Wiley Publication: January 24, 2013
Imprint: Wiley-ISTE Language: English
Author: Amparo Albalate, Wolfgang Minker
ISBN: 9781118586136
Publisher: Wiley
Publication: January 24, 2013
Imprint: Wiley-ISTE
Language: English

This book provides a detailed and up-to-date overview on classification and data mining methods. The first part is focused on supervised classification algorithms and their applications, including recent research on the combination of classifiers. The second part deals with unsupervised data mining and knowledge discovery, with special attention to text mining. Discovering the underlying structure on a data set has been a key research topic associated to unsupervised techniques with multiple applications and challenges, from web-content mining to the inference of cancer subtypes in genomic microarray data. Among those, the book focuses on a new application for dialog systems which can be thereby made adaptable and portable to different domains. Clustering evaluation metrics and new approaches, such as the ensembles of clustering algorithms, are also described.

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This book provides a detailed and up-to-date overview on classification and data mining methods. The first part is focused on supervised classification algorithms and their applications, including recent research on the combination of classifiers. The second part deals with unsupervised data mining and knowledge discovery, with special attention to text mining. Discovering the underlying structure on a data set has been a key research topic associated to unsupervised techniques with multiple applications and challenges, from web-content mining to the inference of cancer subtypes in genomic microarray data. Among those, the book focuses on a new application for dialog systems which can be thereby made adaptable and portable to different domains. Clustering evaluation metrics and new approaches, such as the ensembles of clustering algorithms, are also described.

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