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clustering.evaluation.ClusterCriterion class

Package: clustering.evaluation

Clustering evaluation object

Description

Create a clustering evaluation object using evalclusters.

Properties

ClusteringFunction

Clustering algorithm used to cluster the input data, stored as a valid clustering algorithm name or function handle. If the clustering solutions are provided in the input, ClusteringFunction is empty.

CriterionName

Name of the criterion used for clustering evaluation, stored as a valid criterion name.

CriterionValues

Criterion values corresponding to each proposed number of clusters in InspectedK, stored as a vector of numerical values.

InspectedK

List of the number of proposed clusters for which to compute criterion values, stored as a vector of positive integer values.

Missing

Logical flag for excluded data, stored as a column vector of logical values. If Missing equals true, then the corresponding value in the data matrix x is not used in the clustering solution.

NumObservations

Number of observations in the data matrix X, minus the number of missing (NaN) values in X, stored as a positive integer value.

OptimalK

Optimal number of clusters, stored as a positive integer value.

OptimalY

Optimal clustering solution corresponding to OptimalK, stored as a column vector of positive integer values. If the clustering solutions are provided in the input, OptimalY is empty.

X

Data used for clustering, stored as a matrix of numerical values.

Methods

addKEvaluate additional numbers of clusters
compactCompact clustering evaluation object
plot Plot clustering evaluation object criterion values
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