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LearnClust  

Learning Hierarchical Clustering Algorithms
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("LearnClust", "1.1")



Attach the package and use:
library("LearnClust")
Maintained by
Roberto Alcantara
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-30
Latest Update: 2020-11-29
Description:
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.
How to cite:
Roberto Alcantara (2020). LearnClust: Learning Hierarchical Clustering Algorithms. R package version 1.1, https://cran.r-project.org/web/packages/LearnClust. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0 (2020-09-30 11:30)
Other packages that cited LearnClust R package
View LearnClust citation profile
Other R packages that LearnClust depends, imports, suggests or enhances
Complete documentation for LearnClust
Functions, R codes and Examples using the LearnClust R package
Some associated functions: agglomerativeHC.details . agglomerativeHC . canberradistance.details . canberradistance . canberradistanceW.details . canberradistanceW . chebyshevDistance.details . chebyshevDistance . chebyshevDistanceW.details . chebyshevDistanceW . clusterDistance.details . clusterDistance . clusterDistanceByApproach.details . clusterDistanceByApproach . complementaryClusters.details . complementaryClusters . correlationHC.details . correlationHC . distances.details . distances . divisiveHC.details . divisiveHC . edistance.details . edistance . edistanceW.details . edistanceW . getCluster.details . getCluster . getClusterDivisive.details . getClusterDivisive . initClusters.details . initClusters . initData.details . initData . initImages . initTarget.details . initTarget . matrixDistance . maxDistance.details . maxDistance . mdAgglomerative.details . mdAgglomerative . mdDivisive.details . mdDivisive . mdistance.details . mdistance . mdistanceW.details . mdistanceW . minDistance.details . minDistance . newCluster.details . newCluster . normalizeWeight.details . normalizeWeight . octileDistance.details . octileDistance . octileDistanceW.details . octileDistanceW . toList.details . toList . toListDivisive.details . toListDivisive . usefulClusters . 
Some associated R codes: agglomerativeHC.R . agglomerativeHC.details.R . canberraDistance.R . canberraDistance.details.R . canberraDistanceW.R . canberraDistanceW.details.R . chebyshevDistance.R . chebyshevDistance.details.R . chebyshevDistanceW.R . chebyshevDistanceW.details.R . clusterDistance.R . clusterDistance.details.R . clusterDistanceByApproach.R . clusterDistanceByApproach.details.R . complementaryClusters.R . complementaryClusters.details.R . correlationHC.R . correlationHC.details.R . distances.R . distances.details.R . divisiveHC.R . divisiveHC.details.R . eDistanceW.R . eDistanceW.details.R . euclideanDistance.R . euclideanDistance.details.R . getCluster.R . getCluster.details.R . getClusterDivisive.R . getClusterDivisive.details.R . initClusters.R . initClusters.details.R . initData.R . initData.details.R . initImages.R . initTarget.R . initTarget.details.R . manhattanDistance.R . manhattanDistance.details.R . manhattanDistanceW.R . manhattanDistanceW.details.R . matrixDistance.R . maxDistance.R . maxDistance.details.R . mdAgglomerative.R . mdAgglomerative.details.R . mdDivisive.R . mdDivisive.details.R . minDistance.R . minDistance.details.R . newCluster.R . newCluster.details.R . normalizeWeight.R . normalizeWeight.details.R . octileDistance.R . octileDistance.details.R . octileDistanceW.R . octileDistanceW.details.R . toList.R . toList.details.R . toListDivisive.R . toListDivisive.details.R . usefulClusters.R .  Full LearnClust package functions and examples
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