dcem_star_cluster_uv: dcem_star_cluster_uv (univariate data): Part of DCEM package.

In parichit/DCEM: Clustering Big Data using Expectation Maximization Star (EM*) Algorithm

Description

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

Usage

dcem_star_cluster_uv(data, meu, sigma, prior, num_clusters, num_data,
iteration_count)

Arguments

data	(matrix): The dataset provided by the user.
meu	(vector): The vector containing the initial meu.
sigma	(vector): The vector containing the initial standard deviation.
prior	(vector): The vector containing the initial priors.
num_clusters	(numeric): The number of clusters specified by the user. Default is 2.
num_data	(numeric): number of rows in the dataset (After processing the missing values).
iteration_count	(numeric): The number of iterations for which the algorithm should run. If the convergence is not achieved then the algorithm stops. Default is 100.

Value

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

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

2. (2) Meu: meu: It is a vector of meu. Each element of the vector corresponds to one meu.

3. (3) Sigma: Standard-deviation(s): sigma

   For univariate data: Vector of standard deviation.

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

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

References

Parichit Sharma, Hasan Kurban, Mehmet Dalkilic DCEM: An R package for clustering big data via data-centric modification of Expectation Maximization, SoftwareX, 17, 100944 URL https://doi.org/10.1016/j.softx.2021.100944

parichit/DCEM documentation built on Jan. 22, 2022, 6:13 p.m.