Statistics: SilhouetteEvaluation

### Class Definition: `SilhouetteEvaluation`

Function File: obj = evalclusters (x, clust, `silhouette`)
Function File: obj = evalclusters (…, `Name`, `Value`)

A silhouette object to evaluate clustering solutions.

A `SilhouetteEvaluation` object is a `ClusterCriterion` object used to evaluate clustering solutions using the silhouette criterion.

List of public properties specific to `SilhouetteEvaluation`:

``Distance``

a valid distance metric name, or a function handle or a numeric array as generated by the `pdist` function.

``ClusterPriors``

a valid name for the evaluation of silhouette values: `empirical` (default) or `equal`.

``ClusterSilhouettes``

a cell array with the silhouette values of each data point for each cluster number.

The best solution according to the silhouette criterion is the one that scores the highest average silhouette value.

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

Source Code: SilhouetteEvaluation

### Method: `addK`

SilhouetteEvaluation: obj = addK (obj, K)

Add a new cluster array to inspect the SilhouetteEvaluation object.

### Method: `compact`

SilhouetteEvaluation: obj = compact (obj)

Return a compact SilhouetteEvaluation object (not implemented yet).

### Method: `plot`

SilhouetteEvaluation: plot (obj)
SilhouetteEvaluation: h = plot (obj)

Plot the evaluation results.

Plot the CriterionValues against InspectedK from the SilhouetteEvaluation ClusterCriterion, obj, to the current plot. It can also return a handle to the current plot.