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Data Mining

  • Hardcover
Data mining is a rapidly growing research area in computer science and statistics. Volume 2 of this three-volume series covers theoretical aspects of the subject, including statistical, Bayesian, time-series and others relevant to health informatics.
Data Mining
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There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled "Data Mining: Foundations and Intelligent Paradigms: Volume 2: Core Topics including Statistical, Time-Series and Bayesian Analysis" we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
From the content: Data Mining with Multilayer Perceptrons and Support Vector Machines.- Regulatory Networks under Ellipsoidal Uncertainty - Data Analysis and Prediction by Optimization Theory and Dynamical Systems.- A Visual Environment for Designing and Running Data Mining Workflows in the Knowledge Grid.- Formal framework for the Study of Algorithmic Properties of Objective Interestingness Measures.- Nonnegative Matrix Factorization: Models, Algorithms and Applications.- Visual Data Mining and Discovery with Binarized Vectors.
Pages
264
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Series
Intelligent Systems Reference Library
Year
2011
Edition
2012th
ISBN-10
364223240X
ISBN-13
9783642232404
Format
Hardcover
Publication Date
2011-11-07
Imprint
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Place of Publication
Berlin
Country of Publication
Germany
Edited by
Dawn E. Holmes, Lakhmi C. Jain
DEWEY
006.312
Affiliation
University of California
Short Title
DATA MINING FOUNDATIONS & INTE
Edition Description
2012
Language
English
Media
Book
Series Number
24
Subtitle
VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects
Illustrations
biography
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