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Data Mining: Foundations and Intelligent Paradigms: VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects de Dawn E. Holmes

Data Mining: Foundations and Intelligent Paradigms: VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects: Intelligent Systems Reference Library, cartea 24

Editat de Dawn E. Holmes, Lakhmi C Jain
en Limba Engleză Paperback – 26 ian 2014
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.
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Specificații

ISBN-13: 9783642434297
ISBN-10: 3642434290
Pagini: 264
Ilustrații: XIV, 250 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.37 kg
Ediția:2012
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Intelligent Systems Reference Library

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.

Textul de pe ultima copertă

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.

Caracteristici

contains the latest research on data mining research and its applications to health informatics The state of the art of data mining for health informatics is presented in a handbook style Written by leading experts in this field