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Performs cluster analysis using an ensemble clustering framework, Chiu & Talhouk (2018) <doi:10.1186/s12859-017-1996-y>. Results from a diverse set of algorithms are pooled together using methods such as majority voting, K-Modes, LinkCluE, and CSPA. There are options to compare cluster assignments across algorithms using internal and external indices, visualizations such as heatmaps, and significance testing for the existence of clusters.

copied from cf-post-staging / r-dicer
Type Size Name Uploaded Downloads Labels
conda 1.3 MB | win-64/r-dicer-3.1.0-r43hd8a2815_0.conda  1 month and 18 hours ago 27 main
conda 1.3 MB | osx-64/r-dicer-3.1.0-r43h813e631_0.conda  1 month and 18 hours ago 18 main
conda 1.3 MB | win-64/r-dicer-3.1.0-r44hd8a2815_0.conda  1 month and 18 hours ago 23 main
conda 1.3 MB | osx-64/r-dicer-3.1.0-r44h813e631_0.conda  1 month and 18 hours ago 20 main
conda 1.3 MB | linux-64/r-dicer-3.1.0-r44h3697838_0.conda  1 month and 18 hours ago 83 main
conda 1.3 MB | linux-64/r-dicer-3.1.0-r43h3697838_0.conda  1 month and 18 hours ago 91 main

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