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partitionComparison (version 0.2.6)

Implements Measures for the Comparison of Two Partitions

Description

Provides several measures ((dis)similarity, distance/metric, correlation, entropy) for comparing two partitions of the same set of objects. The different measures can be assigned to three different classes: Pair comparison (containing the famous Jaccard and Rand indices), set based, and information theory based. Many of the implemented measures can be found in Albatineh AN, Niewiadomska-Bugaj M and Mihalko D (2006) and Meila M (2007) . Partitions are represented by vectors of class labels which allow a straightforward integration with existing clustering algorithms (e.g. kmeans()). The package is mostly based on the S4 object system.

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Install

install.packages('partitionComparison')

Monthly Downloads

173

Version

0.2.6

License

MIT + file LICENSE

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Maintainer

Fabian Ball

Last Published

August 23rd, 2023

Functions in partitionComparison (0.2.6)

jaccardCoefficient

Jaccard Coefficient
baulieu1

Baulieu Index 1
gammaStatistics

Gamma Statistics
adjustedRandIndex

Adjusted Rand Index
Partition-class

Simple S4 class to represent a partition of objects as vector of class labels.
minkowskiMeasure

Minkowski Measure
mcconnaughey

McConnaughey Index
goodmanKruskal

Goodman & Kruskal Index
pearson

Pearson Index
partitionComparison-package

partitionComparison: Implements Measures for the Comparison of Two Partitions
compareAll

Compare two partitions with all measures
classificationErrorDistance

Classification Error Distance
gowerLegendre

Gower & Legendre Index
russelRao

Russel & Rao Index
baulieu2

Baulieu Index 2
fagerMcGowan

Fager & McGowan Index
hamann

Hamann Coefficient
kulczynski

Kulczynski Index
larsenAone

Larsen & Aone Measure
randIndex

Rand Index
normalizedLermanIndex

Normalized Lerman Index
normalizedMutualInformation

Normalized Mutual Information
registerPartitionVectorSignatures

Make comparison measures usable with any vectors
wallaceI

Wallace I
lermanIndex

Lerman Index
rvCoefficient

RV Coefficient
sokalSneath1

Sokal & Sneath Index 1
mirkinMetric

Mirkin Metric
[<-,Partition-method

Subsetting Partition instances
variationOfInformation

Variation of Information
sokalSneath2

Sokal & Sneath Index 2
wallaceII

Wallace II
sokalSneath3

Sokal & Sneath Index 3
rogersTanimoto

Rogers & Tanimoto Index
mutualInformation

Mutual Information
projectionNumber

Compute the projection number of two partitions
folwkesMallowsIndex

Folwkes & Mallows Index
peirce

Peirce Index
N01

Method to retrieve the coefficient \(N_{01}\)
N21

Method to retrieve the complex coefficient \(N_{21}\)
N

Method to retrieve the complex coefficient \(N\)
N11

Method to retrieve the coefficient \(N_{11}\)
N12

Method to retrieve the complex coefficient \(N_{12}\)
N00

Method to retrieve the coefficient \(N_{00}\)
dongensMetric

Dongen's Metric
computePairCoefficients

Compute the four coefficients \(N_{11}\), \(N_{10}\), \(N_{01}\), \(N_{00}\)
PairCoefficients-class

S4 class to represent coefficients of object pairs for the comparison of two object partitions (say \(P\) and \(Q\)).
N10

Method to retrieve the coefficient \(N_{10}\)
N01p

Method to retrieve the complex coefficient \(N'_{01}\)
N10p

Method to retrieve the complex coefficient \(N'_{10}\)
entropy

Entropy
czekanowski

Czekanowski Index