Data Mining: Foundations and Intelligent Paradigms

Data mining is a rapidly growing research area in computer science and statistics. Volume 2 of this three-volume series covers theoretical aspects of the subject, including statistical, Bayesian, time-series and others relevant to health informatics.

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.