Data Mining: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification
Dawn E. Holmes , Lakhmi C Jain Publication Date: November 11, 2011 | ISBN-10: 3642231659 | ISBN-13: 978-3642231650 | Edition: 2012
Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 1of this three volume series, we have brought together contributions from some of the most prestigious researchers in the fundamental data mining tasks of clustering, association and classification. Each of the chapters is self contained. Theoreticians and applied scientists/ engineers will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in these aspects of data mining.
Data Mining: Foundations and Intelligent Paradigms: VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects
Dawn E. Holmes , Lakhmi C. Jain Publication Date: November 11, 2011 | ISBN-10: 364223240X | ISBN-13: 978-3642232404 | Edition: 2012
Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 2 of this three volume series, we have brought together contributions from some of the most prestigious researchers in theoretical data mining. Each of the chapters is self contained. Statisticians and applied scientists/ engineers will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in data mining.
Data Mining: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications
Dawn E. Holmes , Lakhmi C Jain Publication Date: January 11, 2012 | ISBN-10: 3642231500 | ISBN-13: 978-3642231506 | Edition: 2012
Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 3 of this three volume series, we have brought together contributions from some of the most prestigious researchers in applied data mining. Areas of application covered are diverse and include healthcare and finance. Each of the chapters is self contained. Statisticians, applied scientists/ engineers and researchers in bioinformatics will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in applied data mining.
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