MOCCA: Multi-objective optimization for collecting cluster alternatives
Version 1.2

This package provides methods to analyze cluster alternatives based on multi-objective optimization of cluster validation indices.

AuthorJohann Kraus <johann.kraus@uni-ulm.de>
Date of publication2012-12-24 15:51:32
MaintainerHans Kestler <hans.kestler@uni-ulm.de>
LicenseArtistic License 2.0
Version1.2
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("MOCCA")

Getting started

Package overview

Popular man pages

analyzePareto: Analyze the Pareto-optimal cluster sizes
mocca: Multi-objective optimization for collecting cluster...
MOCCA-package: Multi-objective optimization for collecting cluster...
toy5: Toy data set with 5 clusters
toy9: Toy data set with 9 clusters
See all...

All man pages Function index File listing

Man pages

analyzePareto: Analyze the Pareto-optimal cluster sizes
mocca: Multi-objective optimization for collecting cluster...
MOCCA-package: Multi-objective optimization for collecting cluster...
toy5: Toy data set with 5 clusters
toy9: Toy data set with 9 clusters

Functions

MOCCA Man page
MOCCA-package Man page
analyzePareto Man page Source code
clusval Source code
create_objectives Source code
cross.quant.similarity Source code
dominate Source code
extract_index Source code
getParetoRanking Source code
getParetoSet Source code
mocca Man page Source code
mocca.boot Source code
mocca.clust Source code
mocca.objectives Source code
mocca.pareto Source code
mocca.validate Source code
na.omit.mocca.objectives Source code
nondominated Source code
plot.mocca.objectives Source code
predict_baseline Source code
predict_cclust Source code
predict_kmeans Source code
predict_single Source code
runcluster Source code
toy5 Man page
toy9 Man page

Files

MD5
R
R/utils.R
R/core.R
NAMESPACE
man
man/toy9.Rd
man/toy5.Rd
man/mocca.Rd
man/MOCCA-package.Rd
man/analyzePareto.Rd
DESCRIPTION
data
data/toy9.RData
data/toy5.RData
MOCCA documentation built on May 19, 2017, 8:52 a.m.

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