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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "GMKMcharlie" in publications use:'
type: software
license: GPL-3.0-only
title: 'GMKMcharlie: Unsupervised Gaussian Mixture and Minkowski and Spherical K-Means
  with Constraints'
version: 1.1.5
doi: 10.32614/CRAN.package.GMKMcharlie
abstract: 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) <https://doi.org/10.1109/34.990138>. These trainers accept
  additional constraints on mixture weights, covariance eigen ratios and on which
  mixture components are subject to update. 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 typical implementations of GM and KM algorithms in various aspects. It is carefully
  crafted in multithreaded C++ for modeling large data for industry use.
authors:
- family-names: Liu
  given-names: Charlie Wusuo
  email: liuwusuo@gmail.com
- email: liuwusuo@gmail.com
repository: https://CRAN.R-project.org/package=GMKMcharlie
date-released: '2021-05-29'
contact:
- family-names: Liu
  given-names: Charlie Wusuo
  email: liuwusuo@gmail.com
- email: liuwusuo@gmail.com