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Finding Groups in Data: An Introduction to Cluster Analysis Leonard Kaufman, Peter J. Rousseeuw
Publisher: Wiley-Interscience

€�Finding Groups in Data: An Introduction to Cluster Analysis” JohnWiley & Sons, New York. Our goal was to establish an organizational classification which would group PHC organizations based on their common characteristics. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. €� John Wiley & Sons, 1990 Collective Intelligence. Clustering Large and High Dimensional data. The organizational data were analyzed .. The information obtained from the organizational survey enabled us to characterize PHC organizations. Because the clustering method failed to separate the patient data into groups by obvious traditional physiological definitions these results confirm our hypothesis that clustering would find meaningful patterns of data that were otherwise impossible to physiologically discern or classify using traditional clinical definitions. Finding Groups in Data: An Introduction to Cluster Analysis. Blashfield RK: Finding groups in data - an introduction to cluster-analysis - Kaufman, L, Rousseeuw, PJ. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis, John Wiley & Sons, Hoboken, NJ, USA, 2005. Kogan J., Nicholas C., Teboulle M. The Wiley–Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. Cluster analysis of the allele-specific expression ratios of X-linked genes in F1 progeny from AKR and PWD reciprocal crosses. This cluster technique has the benefit over the more commonly used k-means and k-medoid cluster analysis, and other grouping methods, in that it allocates a membership value (in the form of a probability value) for each possible construct-cluster pairing rather than simply assigning a construct to a single cluster, thereby the membership of items to more than one group could be Kaufman L, Rousseeuw PJ: Finding groups in data: an introduction to data analysis.