robustEM: Robust EM Algorithm

In AmIACommonGuy/RobustEM: Robust Expectation Maximization Algorithm against Outliers

Robust EM Algorithm

Description

Calculate the mean and covariance matrix of each cluster based on the data matrix.

Usage

robustEM(datamat, cluster, lambda = 3, EM = EM_alg_GMM)

Arguments

datamat	The matrix of points to be clustered.
cluster	Number of clusters
lambda	Regularization Parameter

Value

A list of results, include:

Updated mean vectors for each cluster

Updated covariances for each cluster

Probability of each point in each cluster(a cluster*n matrix)

Number of clusters (cluster)

Dimension (d)

Number of points (n)

Examples

sim_info <- simMultGauss(n = 120, d = 2, cluster = 6, out_perc = 0.03, out_mag = 4)
result <- robustEM(sim_info[["simdata"]], cluster = 6)

AmIACommonGuy/RobustEM documentation built on April 24, 2022, 5:38 a.m.