Grouping Multidimensional Data: Recent Advances in Clustering by Jacob Kogan (Editor), Charles Nicholas (Editor), Marc Teboulle (Editor)
Publisher: Springer; 1 edition (February 10, 2006) | ISBN-10: 354028348X | PDF | 3,7 Mb | 268 pages
Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection. Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques.