Semi-supervised and unsupervised machine learning : novel strategies /

• Main Author: Albalate, Amparo
• Other Authors: Minker, Wolfgang
• Format: eBook
• Language: English
• Published: London : ISTE ; 2011.; Hoboken, NJ : Wiley, 2011.
• Subjects: Data mining.; Discourse analysis > Statistical methods.; Speech processing systems.; Computational intelligence.; Machine learning.; Computational learning theory.; Supervised learning (Machine learning); COMPUTERS > Enterprise Applications > Business Intelligence Tools.; COMPUTERS > Intelligence (AI) & Semantics.; Discourse analysis / Statistical methods.; Electronic books.
• Physical Description: 1 online resource (x, 244 pages) : illustrations
• Bibliography: Includes bibliographical references and index.
• ISBN: 9781118557693; 1118557697; 9781118586334; 1118586336; 9781118586136; 1118586131
• DOI: 10.1002/9781118557693

"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"--