Data Mining: Foundations and Intelligent Paradigms
Statistical, Bayesian, Time Series and other Theoretical Aspects
(Sprache: Englisch)
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.
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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.
Klappentext zu „Data Mining: Foundations and Intelligent Paradigms “
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.
Inhaltsverzeichnis zu „Data Mining: Foundations and Intelligent Paradigms “
- 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
Bibliographische Angaben
- 2011, 2012, 250 Seiten, Maße: 16 x 24,1 cm, Gebunden, Englisch
- Herausgegeben: Lakhmi C Jain, Dawn E. Holmes
- Verlag: Springer
- ISBN-10: 364223240X
- ISBN-13: 9783642232404
- Erscheinungsdatum: 07.11.2011
Sprache:
Englisch
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