Finding Groups in Data: An Introduction to Cluster Analysis book download
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Finding Groups in Data: An Introduction to Cluster Analysis by Leonard Kaufman, Peter J. Rousseeuw
Finding Groups in Data: An Introduction to Cluster Analysis Leonard Kaufman, Peter J. Rousseeuw ebook
Page: 355
Publisher: Wiley-Interscience
Format: pdf
ISBN: 0471735787, 9780471735786
It addresses the following general problem: given a set of entities, find subsets, or clusters, which are homogeneous and/or well separated (cf. In Section 3.2, we introduce the Minimum Covariance Distance (MCD) method for robust correlation. Kaufman L, Rousseeuw PJ: Finding Groups in Data: An Introduction to Cluster Analysis. Hoboken, NJ: John Wiley & Sons, Inc; 1990:1986. It is undoubtedly both an excellent inroduction to and a. Finding Groups in Data: An Introduction to Cluster Analysis (Wiley. The analysis documented in this report is a large-scale application of statistical outlier detection for determining unusual port- specific network behavior. The method uses a robust correlation measure to cluster related ports and to control for the .. Clustering is a powerful tool for automated analysis of data. Jolliffe IT: Principal Component Analysis. In Section 3.3, we introduce local hierarchical clustering for finding groups of related ports.