dcem_cluster_mv: dcem_cluster (multivariate data): Part of DCEM package.

Description Usage Arguments Value Author(s) References

View source: R/dcem_cluster_mv.R

Description

Implements the Expectation Maximization algorithm for multivariate data. This function is called by the dcem_train routine.

Usage

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dcem_cluster_mv(data, meu, sigma, prior, num_clusters, iteration_count,
threshold, num_data)

Arguments

data

A matrix: The dataset provided by the user.

meu

(matrix): The matrix containing the initial meu(s).

sigma

(list): A list containing the initial covariance matrices.

prior

(vector): A vector containing the initial prior.

num_clusters

(numeric): The number of clusters specified by the user. Default value is 2.

iteration_count

(numeric): The number of iterations for which the algorithm should run, if the convergence is not achieved then the algorithm stops. Default: 200.

threshold

(numeric): A small value to check for convergence (if the estimated meu are within this specified threshold then the algorithm stops and exit).

Note: Choosing a very small value (0.0000001) for threshold can increase the runtime substantially and the algorithm may not converge. On the other hand, choosing a larger value (0.1) can lead to sub-optimal clustering. Default: 0.00001.

num_data

(numeric): The total number of observations in the data.

Value

A list of objects. This list contains parameters associated with the Gaussian(s) (posterior probabilities, meu, co-variance and prior)

  1. (1) Posterior Probabilities: prob :A matrix of posterior-probabilities.

  2. (2) Meu: meu: It is a matrix of meu(s). Each row in the matrix corresponds to one meu.

  3. (3) Sigma: Co-variance matrices: sigma

  4. (4) prior: prior: A vector of prior.

Author(s)

Parichit Sharma [email protected], Hasan Kurban, Mark Jenne, Mehmet Dalkilic

This work is partially supported by NCI Grant 1R01CA213466-01.

References

Using data to build a better EM: EM* for big data.

Hasan Kurban, Mark Jenne, Mehmet M. Dalkilic (2016) <https://doi.org/10.1007/s41060-017-0062-1>.


parichit/DCEM documentation built on Feb. 28, 2020, 11:47 p.m.