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.
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.
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Intelligent Systems Reference Library
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Place of Publication
Country of Publication
Dawn E. Holmes, Lakhmi C. Jain
University of California
DATA MINING FOUNDATIONS & INTE
VOLUME 2: Statistical, Bayesian, Time Series and other Theoretical Aspects