dcem_star_cluster_uv {DCEM} | R Documentation |
dcem_star_cluster_uv (univariate data): Part of DCEM package.
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) Posterior Probabilities: prob A matrix of posterior-probabilities
(2) Meu: meu: It is a vector of meu. Each element of the vector corresponds to one meu.
(3) Sigma: Standard-deviation(s): sigma
For univariate data: Vector of standard deviation.
(4) Priors: prior: A vector of priors.
(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