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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 9 hours ago 26 main
conda 1.3 MB | osx-64/r-dicer-3.1.0-r43h813e631_0.conda  1 month and 9 hours ago 17 main
conda 1.3 MB | win-64/r-dicer-3.1.0-r44hd8a2815_0.conda  1 month and 9 hours ago 22 main
conda 1.3 MB | osx-64/r-dicer-3.1.0-r44h813e631_0.conda  1 month and 9 hours ago 19 main
conda 1.3 MB | linux-64/r-dicer-3.1.0-r44h3697838_0.conda  1 month and 9 hours ago 82 main
conda 1.3 MB | linux-64/r-dicer-3.1.0-r43h3697838_0.conda  1 month and 9 hours ago 89 main

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