dcem_test {DCEM}

dcem_test: Part of DCEM package.

Description

For demonstrating the execution on the bundled dataset.

Usage

dcem_test()

Details

The dcem_test performs the following steps in order:

1. Read the data from the disk (from the file data/ionosphere_data.csv). The data folder is under the package installation folder.

2. The dataset details can be see by typing ionosphere_data in R-console or at http://archive.ics.uci.edu/ml/datasets/Ionosphere.

3. Clean the data (by removing the columns). The data should be cleaned before use. Refer trim_data to see what columns should be removed and how. The package provides the basic interface for removing columns.

4. Call the dcem_star_train on the cleaned data.

Accessing the output parameters

The function dcem_test() calls the dcem_star_train. It returns a list of objects as output. This list contains estimated parameters of the Gaussian (posterior probabilities, meu, sigma and prior). The parameters can be accessed as follows where sample_out is the list containing the output:

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

2. (2) Meu: meu

   For multivariate data: It is a matrix of meu(s). Each row in the matrix corresponds to one meu.

3. (3) Co-variance matrices: sample_out$sigma

   For multivariate data: List of co-variance matrices for the Gaussian(s).

   Standard-deviation: sample_out$sigma

   For univariate data: Vector of standard deviation for the Gaussian(s))

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

5. (5) Membership: sample_out$membership: A dataframe of cluster membership for data. Columns numbers are data indices and values are the assigned clusters.

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