Data Mining: Foundations and Intelligent Paradigms VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects
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. Statisti...
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2012, 2012
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| Edition: | 1st ed. 2012 |
| Series: | Intelligent Systems Reference Library
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
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