EMCluster: Expectation Maximization Clustering

In Evacluster: Evaluation Clustering Methods for Disease Subtypes Diagnosis

Expectation Maximization Clustering

Description

This function perform EM algorithm for model-based clustering of finite mixture multivariate Gaussian distribution.The general purpose of clustering is to detect clusters of data and to assign the data to the clusters.

Usage

EMCluster(data = NULL, ...)

Arguments

data	A Data set
...	k: The number of Clusters

Value

A list of cluster labels and a returned object from init.EM

Examples

library(datasets)
data(iris)

rndSamples <- sample(nrow(iris),100)
trainData <- iris[rndSamples,]
testData <- iris[-rndSamples,]

clsut <- EMCluster(trainData[,1:4],3)

Evacluster documentation built on April 1, 2022, 9:07 a.m.