DCEM: Clustering Big Data using Expectation Maximization Star (EM*)Algorithm
Implements the Improved Expectation Maximisation EM* and the traditional EM algorithm for clustering big data (gaussian mixture models for both multivariate and univariate datasets). This version implements the faster alternative-EM* that expedites convergence via structure based data segregation. The implementation supports both random and K-means++ based initialization. Reference: Parichit Sharma, Hasan Kurban, Mehmet Dalkilic (2022) <doi:10.1016/j.softx.2021.100944>. Hasan Kurban, Mark Jenne, Mehmet Dalkilic (2016) <doi:10.1007/s41060-017-0062-1>.
| Version: | 2.0.5 |
| Depends: | R (≥ 3.2.0) |
| Imports: | mvtnorm (≥ 1.0.7),matrixcalc (≥ 1.0.3),MASS (≥ 7.3.49),Rcpp (≥ 1.0.2) |
| LinkingTo: | Rcpp |
| Suggests: | knitr,rmarkdown |
| Published: | 2022-01-16 |
| DOI: | 10.32614/CRAN.package.DCEM |
| Author: | Sharma Parichit [aut, cre, ctb], Kurban Hasan [aut, ctb], Dalkilic Mehmet [aut] |
| Maintainer: | Sharma Parichit <parishar at iu.edu> |
| BugReports: | https://github.com/parichit/DCEM/issues |
| License: | GPL-3 |
| URL: | https://github.com/parichit/DCEM |
| NeedsCompilation: | yes |
| Citation: | DCEM citation info |
| Materials: | README,NEWS |
| CRAN checks: | DCEM results |
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