Cluster Analysis For Data Mining And System Identification

Download Cluster Analysis For Data Mining And System Identification PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Cluster Analysis For Data Mining And System Identification book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Cluster Analysis for Data Mining and System Identification

Author: János Abonyi
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-06-22
The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.
Cluster Analysis for Data Mining and System Identification

Author: János Abonyi
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-08-10
The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.
Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection

Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.