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Comprehensive cluster analysis with Transitivity Clustering
Nature Protocols, 2011Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a ...
Tobias, Wittkop +5 more
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The Literature On Cluster Analysis
Multivariate Behavioral Research, 1978There has been an explosion of interest in cluster analysis since 1960. The "explosion" of this literature is documented through: (a) a rapid growth in the number of articles which have been published using this technique; (b) the wide range of sciences interested in clustering; (c) the large and growing number of software programs for performing ...
R K, Blashfield, M S, Aldenderfer
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Veterinary Immunology and Immunopathology, 1996
Cluster analysis was performed on flow cytometry data generated from the reactivities of the 302 workshop monoclonal antibodies with 36 target cell preparations. The antibodies were assigned to 42 preliminary clusters that were subjected to further examination in subsequent stages of the workshop.
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Cluster analysis was performed on flow cytometry data generated from the reactivities of the 302 workshop monoclonal antibodies with 36 target cell preparations. The antibodies were assigned to 42 preliminary clusters that were subjected to further examination in subsequent stages of the workshop.
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Multivariate Behavioral Research, 1970
Different applicatiions require different systems of cluster analysis. The ways in which systems differ are pointed out. The present system was designed originally; to identify, in a homogeneous callection of questionnaire or inventory items or of tests, groups of items which can be scored as subtests, or groups of tests which can be combined to yield ...
E E, Cureton, L W, Cureton, R C, Durfee
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Different applicatiions require different systems of cluster analysis. The ways in which systems differ are pointed out. The present system was designed originally; to identify, in a homogeneous callection of questionnaire or inventory items or of tests, groups of items which can be scored as subtests, or groups of tests which can be combined to yield ...
E E, Cureton, L W, Cureton, R C, Durfee
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Biometrics, 1965
A method for investigating the relation of points in multidimensional space is described. Using an analysis of variance technique, the points are divided into the two most-compact clusters, and the pTocess repeated sequentially so that a tree diagram is formed. It is pointed out that the method is well suited to electronic computing. The application of
A W, EDWARDS, L L, CAVALLI-SFORZA
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A method for investigating the relation of points in multidimensional space is described. Using an analysis of variance technique, the points are divided into the two most-compact clusters, and the pTocess repeated sequentially so that a tree diagram is formed. It is pointed out that the method is well suited to electronic computing. The application of
A W, EDWARDS, L L, CAVALLI-SFORZA
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CLUSTER-a package for cluster analysis
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1988The use of different measures of similarity, clusterization criteria, and theories in cluster analysis makes it difficult to compare interpretations of a single data set. The authors present some methods as well as software tools for comparison of cluster partitions.
I. Popchev, V. Peneva
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Clustering Consistency Analysis
Journal of the Academy of Marketing Science, 1982Cluster analysis is a frequently used technique in marketing as a method to develop partitions or classifications for market segmentation, product positioning, test market selection, etc. Because of the vast diversity in the assortment of clustering algorithms available, it is often times not obvious which algorithm or technique should be employed.
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On a Method of Cluster Analysis
1984zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Analytical Chemistry, 1999
This article describes how the concept of multiresolution is used with cluster analysis of spectral data. Multiresolution analysis progressively increases the resolution of a spectrum profile by adding levels of details contained in scales obtained from a discrete wavelet transform.
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This article describes how the concept of multiresolution is used with cluster analysis of spectral data. Multiresolution analysis progressively increases the resolution of a spectrum profile by adding levels of details contained in scales obtained from a discrete wavelet transform.
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Biometrika, 1978
A parametric model for partitioning individuals into mutually exclusive groups is given. A Bayesian analysis is applied and a loss structure imposed. A model-dependent definition of a similarity inatrix is proposed and estimates based on this matrix are justified in a decision-theoretic framework.
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A parametric model for partitioning individuals into mutually exclusive groups is given. A Bayesian analysis is applied and a loss structure imposed. A model-dependent definition of a similarity inatrix is proposed and estimates based on this matrix are justified in a decision-theoretic framework.
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