Data Mining: Foundations and Intelligent Paradigms VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects
Título:
Data Mining: Foundations and Intelligent Paradigms VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects
ISBN:
9783642232411
Edición:
1st ed. 2012.
PRODUCTION_INFO:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Descripción física:
XIV, 250 p. online resource.
Serie:
Intelligent Systems Reference Library, 24
Contenido:
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.
Síntesis:
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.
Término de la materia:
Autor corporativo añadido:
Acceso electrónico:
Full Text Available From Springer Nature Engineering 2012 Packages
Idioma:
Inglés