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  2. Correlation clustering - Wikipedia

    en.wikipedia.org/wiki/Correlation_clustering

    Different methods for correlation clustering of this type are discussed in [12] and the relationship to different types of clustering is discussed in. [13] See also Clustering high-dimensional data. Correlation clustering (according to this definition) can be shown to be closely related to biclustering. As in biclustering, the goal is to ...

  3. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  4. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters).

  5. Automatic clustering algorithms - Wikipedia

    en.wikipedia.org/wiki/Automatic_Clustering...

    Automatic clustering algorithms are algorithms that can perform clustering without prior knowledge of data sets. In contrast with other cluster analysis techniques, automatic clustering algorithms can determine the optimal number of clusters even in the presence of noise and outlier points. [1] [needs context]

  6. Category:Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Category:Cluster_analysis

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  7. Arthur Zimek - Wikipedia

    en.wikipedia.org/wiki/Arthur_Zimek

    His dissertation on "Correlation Clustering" was awarded the "SIGKDD Doctoral Dissertation Award 2009 Runner-up" [2] by the Association for Computing Machinery. He is well known [ 3 ] for his work on outlier detection , [ 4 ] [ 5 ] density-based clustering , [ 6 ] correlation clustering , [ 7 ] [ 8 ] and the curse of dimensionality .

  8. Clustering high-dimensional data - Wikipedia

    en.wikipedia.org/wiki/Clustering_high...

    Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions.Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology can produce many measurements at once, and the clustering of text documents, where, if a word-frequency vector is used, the number of dimensions ...

  9. Canonical correlation - Wikipedia

    en.wikipedia.org/wiki/Canonical_correlation

    In statistics, canonical-correlation analysis (CCA), also called canonical variates analysis, is a way of inferring information from cross-covariance matrices.If we have two vectors X = (X 1, ..., X n) and Y = (Y 1, ..., Y m) of random variables, and there are correlations among the variables, then canonical-correlation analysis will find linear combinations of X and Y that have a maximum ...