Learning Hierarchical Clustering Algorithms

Classical hierarchical clustering algorithms, agglomerative and divisive clustering. Algorithms are implemented as a theoretical way, step by step. It includes some detailed functions that explain each step. Every function allows options to get different results using different techniques. The package explains non expert users how hierarchical clustering algorithms work.


Reference manual

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1.1 by Roberto Alcantara, a year ago

Browse source code at https://github.com/cran/LearnClust

Authors: Roberto Alcantara [aut, cre] , Juan Jose Cuadrado [aut] , Universidad de Alcala de Henares [aut]

Documentation:   PDF Manual  

Unlimited license

Depends on magick

Suggests knitr, rmarkdown

See at CRAN