dcem_star_cluster_mv: dcem_star_cluster_mv (multivariate data): Part of DCEM...

Description Usage Arguments Value Author(s) References

View source: R/dcem_star_cluster_mv.R

Description

Implements the EM* algorithm for multivariate data. This function is called by the dcem_star_train routine.

Usage

1
dcem_star_cluster_mv(data, meu, sigma, prior, num_clusters, iteration_count, num_data)

Arguments

data

(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 priors.

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 and exits. Default: 200.

num_data

(numeric): Number of rows in the dataset.

Value

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

  1. (1) Posterior Probabilities: prob A matrix of posterior-probabilities for the points in the dataset.

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

  3. (3) Sigma: Co-variance matrices: sigma: List of co-variance matrices.

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

  5. (5) Membership: membership: A vector of cluster membership for data.

Author(s)

Parichit Sharma parishar@iu.edu, Hasan Kurban, Mark Jenne, Mehmet Dalkilic

This work is 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>.


DCEM documentation built on Aug. 2, 2020, 9:07 a.m.