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Evacluster (version 0.1.0)

Evaluation Clustering Methods for Disease Subtypes Diagnosis

Description

Contains a set of clustering methods and evaluation metrics to select the best number of the clusters based on clustering stability. Two references describe the methodology: Fahimeh Nezhadmoghadam, and Jose Tamez-Pena (2021), and Fahimeh Nezhadmoghadam, et al.(2021).

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Version

Install

install.packages('Evacluster')

Monthly Downloads

234

Version

0.1.0

License

LGPL (>= 2)

Maintainer

Fahimeh Nezhadmoghadam

Last Published

April 1st, 2022

Functions in Evacluster (0.1.0)

predict.FuzzyCluster

FuzzyCluster prediction function

predict.hierarchicalCluster

hierarchicalCluster prediction function

Partitioning Around Medoids (PAM) Clustering

predict.pamCluster

pamCluster prediction function

predict.EMCluster

EMCluster prediction function

predict.tsneReductor

tsneReductor prediction function

Fuzzy C-means Clustering Algorithm

clusterStability

clustering stability function

predict.nmfCluster

nmfCluster prediction function

predict.kmeansCluster

kmeansCluster prediction function

hierarchicalCluster

hierarchical clustering

getConsensusCluster

Consensus Clustering Results

K-means Clustering

Non-negative matrix factorization (NMF)

t-Distributed Stochastic Neighbor Embedding (t-SNE)

Expectation Maximization Clustering

Evacluster-package

Evaluation Clustering Methods for Disease Subtypes Diagnosis (Evacluster)