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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-2.1.0-r41ha856d6a_0.conda  1 year and 11 months ago 511 main
conda 1.3 MB | osx-64/r-dicer-2.1.0-r43hac7d2d5_0.conda  1 year and 11 months ago 332 main
conda 1.3 MB | osx-64/r-dicer-2.1.0-r42hac7d2d5_0.conda  1 year and 11 months ago 342 main
conda 1.3 MB | linux-64/r-dicer-2.1.0-r43ha503ecb_0.conda  1 year and 11 months ago 1705 main
conda 1.3 MB | linux-64/r-dicer-2.1.0-r42ha503ecb_0.conda  1 year and 11 months ago 1705 main

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