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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-3.0.0-r44h8ae3a7c_0.conda  1 year and 4 months ago 888 main
conda 1.3 MB | osx-64/r-dicer-3.0.0-r44h2711daa_0.conda  1 year and 4 months ago 830 main
conda 1.3 MB | win-64/r-dicer-3.0.0-r43h8ae3a7c_0.conda  1 year and 4 months ago 882 main
conda 1.3 MB | osx-64/r-dicer-3.0.0-r43h2711daa_0.conda  1 year and 4 months ago 820 main
conda 1.3 MB | linux-64/r-dicer-3.0.0-r43h93ab643_0.conda  1 year and 4 months ago 1969 main
conda 1.3 MB | linux-64/r-dicer-3.0.0-r44h93ab643_0.conda  1 year and 4 months ago 1952 main

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