A character vector or a function handle specifying the clustering algorithm used to generate the clustering solutions. It can be empty if the clustering solutions are passed as an input matrix. This property is read-only.

A character vector specifying the name of the criterion used to evaluate the clustering solutions. This property is read-only.

A numeric vector containing the values generated by the evaluation criterion for each clustering solution. This property is read-only.

A numeric vector containing the list of the number of clusters evaluated. This property is read-only.

A logical vector indicating which observations in the data matrix contain missing values (NaN). This property is read-only.

An integer specifying the number of non-missing observations in the data matrix. This property is read-only.

An integer specifying the optimal number of clusters based on the evaluation criterion. This property is read-only.

A numeric vector representing the clustering solution that corresponds to the optimal number of clusters. This property is read-only.

A numeric matrix containing the data used for clustering. This property is read-only.

ClusterCriterion: obj = ClusterCriterion (x, clust, KList)

ClusterCriterion is a superclass and is not meant to be instantiated directly. Use evalclusters instead.

See also: evalclusters

ClusterCriterion: obj = addK (obj, k)

addK adds a new list of cluster numbers, k, to the ClusterCriterion object.

ClusterCriterion: h = plot (obj)

plot generates a plot of the criterion values against the number of clusters.

The optimal number of clusters is marked with an asterisk.

The optional return value, h, is a graphics handle to the plot.

ClusterCriterion: obj = compact (obj)

This method is not yet implemented.