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clustlearn  

Learn Clustering Techniques Through Examples and Code
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("clustlearn", "1.0.0")



Attach the package and use:
library("clustlearn")
Maintained by
Eduardo Ruiz Sabajanes
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-09-14
Latest Update: 2023-09-14
Description:
Clustering methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in Ezugwu et. al., (2022) ; and datasets to test them on, which highlight the strengths and weaknesses of each technique, as presented in the clustering section of 'scikit-learn' (Pedregosa et al., 2011) .
How to cite:
Eduardo Ruiz Sabajanes (2023). clustlearn: Learn Clustering Techniques Through Examples and Code. R package version 1.0.0, https://cran.r-project.org/web/packages/clustlearn. Accessed 21 Nov. 2024.
Previous versions and publish date:
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Other R packages that clustlearn depends, imports, suggests or enhances
Complete documentation for clustlearn
Functions, R codes and Examples using the clustlearn R package
Some associated functions: agglomerative_clustering . db1 . db2 . db3 . db4 . db5 . db6 . dbscan . divisive_clustering . gaussian_mixture . kmeans . 
Some associated R codes: agglomerative_clustering.R . console.R . data.R . dbscan.R . divisive_clustering.R . gaussian_mixture.R . kmeans.R .  Full clustlearn package functions and examples
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