ClusterCriterion is a superclass for clustering evaluation objects as created by evalclusters.

List of public properties:

ClusteringFunction

a valid clustering funtion name or function handle. It can be empty if the clustering solutions are passed as an input matric.

a valid criterion name to evaluate the clustering solutions.

a vector of values as generated by the evaluation criterion for each clustering solution.

the list of proposed cluster numbers.

a logical vector of missing observations. When there are NaN values in the data matrix, the corresponding observation is excluded.

the number of non-missing observations in the data matrix.

the optimal number of clusters.

the clustering solution corresponding to OptimalK.

the data matrix.

List of public methods:

addK

add a list of numbers of clusters to evaluate.

return a compact clustering evaluation object. Not implemented

plot the clustering evaluation values against the corresponding number of clusters.

See also: evalclusters, CalinskiHarabaszEvaluation, DaviesBouldinEvaluation, GapEvaluation, SilhouetteEvaluation

Source Code: ClusterCriterion