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

The grouping process implements a clustering methodology called "Partitioning Around Mediods" as detailed in chapter 2 of L. We performed multivariate (exhaled NO as dependent variable) and k-means cluster analyses in a population of 169 asthmatic children (age ± SD: 10.5 ± 2.6 years) recruited in a monocenter cohort that was characterized in a cross-sectional .. Blashfield RK: Finding groups in data - an introduction to cluster-analysis - Kaufman, L, Rousseeuw, PJ. My research question is about elderly people and I have to find out underlying groups. The data comes from a questionnaire. Finally, we discuss the consequences of our findings for the experimental design of microbiota studies in murine disease models. Kaufman L, Rousseeuw PJ: Finding Groups in Data: An Introduction to Cluster Analysis. It is undoubtedly both an excellent inroduction to and a. Stephan Holtmeier, who is a psychologist by background, presented an introduction to cluster analysis with R, motivated by his work in analysing survey data. Finding Groups in Data: An Introduction to Cluster Analysis (Wiley. Clustering can be considered the most important unsupervised learning problem; so, as every other problem of this kind, it deals with finding a structure in a collection of unlabeled data. Cluster analysis of the allele-specific expression ratios of X-linked genes in F1 progeny from AKR and PWD reciprocal crosses.