ClusterCriterion
A clustering evaluation object as created by evalclusters.
ClusterCriterion is a superclass for clustering evaluation objects
as created by evalclusters.
List of public properties:
ClusteringFunctiona valid clustering funtion name or function handle. It can be empty if the clustering solutions are passed as an input matric.
CriterionNamea valid criterion name to evaluate the clustering solutions.
CriterionValuesa vector of values as generated by the evaluation criterion for each clustering solution.
InspectedKthe list of proposed cluster numbers.
Missing a logical vector of missing observations. When there are NaN
values in the data matrix, the corresponding observation is excluded.
NumObservationsthe number of non-missing observations in the data matrix.
OptimalKthe optimal number of clusters.
OptimalY the clustering solution corresponding to OptimalK.
Xthe data matrix.
List of public methods:
addKadd a list of numbers of clusters to evaluate.
compactreturn a compact clustering evaluation object. Not implemented
plotplot the clustering evaluation values against the corresponding number of clusters.
See also: evalclusters, CalinskiHarabaszEvaluation, DaviesBouldinEvaluation, GapEvaluation, SilhouetteEvaluation
Source Code: ClusterCriterion
addK
Add a new cluster array to inspect the ClusterCriterion object.
compact
Return a compact ClusterCriterion object (not implemented yet).
plot
Plot the evaluation results.
Plot the CriterionValues against InspectedK from the ClusterCriterion, obj, to the current plot. It can also return a handle to the current plot.