Cluster Analysis for Data Mining and System Identification

By Janos Abonyi and Balázs Feil

This book identifies fuzzy cluster analysis as a good approach to solving complex data mining and system identification problems. It illustrates how advanced fuzzy clustering algorithms can be used not only for partitioning of the data, but it can be used for visualization, regression, classification and time-series analysis. Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the classification of similar objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait often proximity according to some defined distance measure.

• Format: Hardcover
• Language: English
• ISBN: 3764379871
• ISBN13: 9783764379872
• Release Date: June 2007
• Publisher: Birkhauser
• Length: 306 Pages
• Weight: 1.45 lbs.
• Dimensions: 0.8" x 6.1" x 9.2"