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...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Holmes, Dawn E. (Editor), Jain, Lakhmi C. (Editor)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.
Series:Intelligent Systems Reference Library, 24
Subjects:
Online Access:Full Text via HEAL-Link
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.