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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 string 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 string.

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

See Also

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