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diceR  

Diverse Cluster Ensemble in R
View on CRAN: Click here


Download and install diceR package within the R console
Install from CRAN:
install.packages("diceR")

Install from Github:
library("remotes")
install_github("cran/diceR")

Install by package version:
library("remotes")
install_version("diceR", "2.2.0")



Attach the package and use:
library("diceR")
Maintained by
Derek Chiu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-22
Latest Update: 2024-01-22
Description:
Performs cluster analysis using an ensemble clustering framework, Chiu & Talhouk (2018) . 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.
How to cite:
Derek Chiu (2017). diceR: Diverse Cluster Ensemble in R. R package version 2.2.0, https://cran.r-project.org/web/packages/diceR
Previous versions and publish date:
0.1.0 (2017-06-22 01:37), 0.2.0 (2017-09-30 01:06), 0.3.0 (2017-11-29 21:06), 0.3.1 (2017-12-12 23:07), 0.3.2 (2018-01-14 17:02), 0.4.0 (2018-02-23 00:44), 0.5.0 (2018-05-05 18:12), 0.5.1 (2018-06-11 11:29), 0.5.2 (2019-03-08 14:42), 0.6.0 (2019-07-25 22:30), 1.0.0 (2020-07-08 00:30), 1.0.1 (2021-01-31 01:30), 1.0.2 (2021-03-19 00:00), 1.0.3 (2021-04-17 09:10), 1.0.4 (2021-06-04 10:30), 1.1.0 (2021-07-23 21:30), 1.2.0 (2022-05-13 10:50), 1.2.1 (2022-08-17 02:10), 1.2.2 (2022-09-29 17:10), 2.0.0 (2023-03-11 09:20), 2.1.0 (2023-09-29 00:40)
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