GapEvaluation
gap)Name, Value)A gap object to evaluate clustering solutions.
A GapEvaluation object is a ClusterCriterion
object used to evaluate clustering solutions using the gap criterion,
which is a mathematical formalization of the elbow method.
List of public properties specific to SilhouetteEvaluation:
Bthe number of reference datasets to generate.
Distance a valid distance metric name, or a function handle as accepted by the
pdist function.
ExpectedLogWa vector of the expected values for the logarithm of the within clusters dispersion.
LogWa vector of the values of the logarithm of the within clusters dispersion.
ReferenceDistribution a valid name for the reference distribution, namely: PCA (default)
or uniform.
SEa vector of the standard error of the expected values for the logarithm of the within clusters dispersion.
SearchMethod a valid name for the search method to use: globalMaxSE (default) or
firstMaxSE.
StdLogWa vector of the standard deviation of the expected values for the logarithm of the within clusters dispersion.
The best solution according to the gap criterion depends on the chosen
search method. When the search method is globalMaxSE, the chosen
gap value is the smaller one which is inside a standard error from the
max gap value; when the search method is firstMaxSE, the chosen
gap value is the first one which is inside a standard error from the next
gap value.
See also: evalclusters, ClusterCriterion, CalinskiHarabaszEvaluation, DaviesBouldinEvaluation, SilhouetteEvaluation
Source Code: GapEvaluation
addK
Add a new cluster array to inspect the GapEvaluation object.
compact
Return a compact GapEvaluation object (not implemented yet).
plot
Plot the evaluation results.
Plot the CriterionValues against InspectedK from the GapEvaluation ClusterCriterion, obj, and show the standard deviation to the current plot. It can also return a handle to the current plot.