Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Cluster Analysis for Data Mining and System Identification

Cluster Analysis for Data Mining and System Identification

Abonyi, János
Feil, Balázs

Hardcover

Business GeneralGeneral MathematicsProbability & Statistics

ISBN10: 3764379871
ISBN13: 9783764379872
Publisher: Springer Nature
Published: Jun 22 2007
Pages: 306
Weight: 1.40
Height: 0.75 Width: 6.14 Depth: 9.21
Language: English

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.

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