Data Mining: Foundations and Intelligent Paradigms: VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects
Author:   Dawn E. Holmes ,  Lakhmi C Jain
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2012 ed.
Volume:   24
ISBN:  

9783642232404


Pages:   250
Publication Date:   07 November 2011
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Data Mining: Foundations and Intelligent Paradigms: VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects


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Overview

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.

Full Product Details

Author:   Dawn E. Holmes ,  Lakhmi C Jain
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2012 ed.
Volume:   24
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   0.613kg
ISBN:  

9783642232404


ISBN 10:   364223240
Pages:   250
Publication Date:   07 November 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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.

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