kamila: Methods for Clustering Mixed-Type Data

Implements methods for clustering mixed-type data, specifically combinations of continuous and nominal data. Special attention is paid to the often-overlooked problem of equitably balancing the contribution of the continuous and categorical variables. This package implements KAMILA clustering, a novel method for clustering mixed-type data in the spirit of k-means clustering. It does not require dummy coding of variables, and is efficient enough to scale to rather large data sets. Also implemented is Modha-Spangler clustering, which uses a brute-force strategy to maximize the cluster separation simultaneously in the continuous and categorical variables.

AuthorAlexander Foss [aut, cre], Marianthi Markatou [aut]
Date of publication2016-08-19 00:46:49
MaintainerAlexander Foss <alexanderhfoss@gmail.com>
LicenseGPL-3
Version0.1.1.1
https://github.com/ahfoss/kamila

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Files

kamila
kamila/tests
kamila/tests/testthat.R
kamila/tests/testthat
kamila/tests/testthat/test_kamila.R
kamila/tests/testthat/test_medea.R
kamila/tests/testthat/test_gmsClust.R
kamila/tests/testthat/test_medea_helper_functions.R
kamila/src
kamila/src/RcppExports.cpp
kamila/src/cppfunctions.cpp
kamila/NAMESPACE
kamila/R
kamila/R/misc_functions.R kamila/R/modha_spangler.R kamila/R/calc_approx_bic_deprec.R kamila/R/RcppExports.R kamila/R/medea.R kamila/R/kamila.R kamila/R/prediction_strength_deprec.R kamila/R/gen_mixed_data.R
kamila/README.md
kamila/MD5
kamila/DESCRIPTION
kamila/man
kamila/man/kamila.Rd kamila/man/genMixedData.Rd kamila/man/wkmeans.Rd kamila/man/gmsClust.Rd kamila/man/kamila-package.Rd kamila/man/classifyKamila.Rd kamila/man/dummyCodeFactorDf.Rd

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