GMKMcharlie v1.0.3

0

Monthly downloads

0th

Percentile

Unsupervised Gaussian Mixture and Minkowski K-Means

High performance trainers for parameterizing and clustering weighted data. The Gaussian mixture (GM) module includes the conventional EM (expectation maximization) trainer, the component-wise EM trainer, the minimum-message-length EM trainer by Figueiredo and Jain (2002) <doi:10.1109/34.990138>. These trainers accept additional constraints on mixture weights and covariance eigen ratios. The K-means (KM) module offers clustering with the options of (i) deterministic and stochastic K-means++ initializations, (ii) upper bounds on cluster weights (sizes), (iii) Minkowski distances, (iv) cosine dissimilarity, (v) dense and sparse representation of data input. The package improved the usual implementations of GM and KM training algorithms in various aspects. It is carefully crafted in multithreaded C++ for processing large data in industry use.

Functions in GMKMcharlie

Name Description
GM Multithreaded Gaussian mixture trainer
KMsparse K-means over sparse representation of data
KMconstrained K-means over dense data input with constraints on cluster weights
KMppIniSparse Minkowski and spherical, deterministic and stochastic, multithreaded K-means++ initialization over sparse representation of data
GMcw Multithreaded component-wise Gaussian mixture trainer
KMppIni Minkowski and spherical, deterministic and stochastic, multithreaded K-means++ initialization over dense representation of data
d2s Dense to sparse conversion
KMconstrainedSparse K-means over sparse data input with constraints on cluster weights
GMfj Multithreaded minimum message length Gaussian mixture trainer
s2d Sparse to dense conversion
KM K-means over dense representation of data
No Results!

Last month downloads

Details

Type Package
License GPL-3
Encoding UTF-8
LazyData true
LinkingTo Rcpp, RcppParallel, RcppArmadillo
SystemRequirements GNU make
NeedsCompilation yes
Packaged 2019-10-03 14:41:05 UTC; i56087
Repository CRAN
Date/Publication 2019-10-08 09:10:03 UTC

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/GMKMcharlie)](http://www.rdocumentation.org/packages/GMKMcharlie)