DaviesBouldinEvaluation
statistics: DaviesBouldinEvaluation
Davies-Bouldin object to evaluate clustering solutions
A DaviesBouldinEvaluation object is a ClusterCriterion
object used to evaluate clustering solutions using the Davies-Bouldin
criterion.
The Davies-Bouldin criterion is based on the ratio between the distances between clusters and within clusters — distances between centroids and distances between each datapoint and its centroid.
The best solution according to the Davies-Bouldin criterion is the one that produces the lowest Davies-Bouldin value.
See also: evalclusters, ClusterCriterion, CalinskiHarabaszEvaluation, GapEvaluation, SilhouetteEvaluation
Source Code: DaviesBouldinEvaluation
DaviesBouldinEvaluation: obj = addK (obj, K)
DaviesBouldinEvaluation: plot (obj)
DaviesBouldinEvaluation: h = plot (obj)
Plot the CriterionValues against InspectedK from the DaviesBouldinEvaluation ClusterCriterion to the current plot. Returns an axes handle if requested.
DaviesBouldinEvaluation: obj = compact (obj)