apclusterK_euclidean: Method that runs the apClusterK algorithm using the Euclidean...

In laperez/Clustering: Techniques for Evaluating Clustering

Method that runs the apClusterK algorithm using the Euclidean metric to make an external or internal validation of the cluster.

Description

Method that runs the apClusterK algorithm using the Euclidean metric to make an external or internal validation of the cluster.

Usage

apclusterK_euclidean(dt, clusters, columnClass, metric)

Arguments

dt	Matrix or data frame with the set of values to be applied to the algorithm.
clusters	It's an integer that indexes the number of clusters we want to create.
metric	It's a characters vector with the metrics avalaible in the package. The metrics implemented are: Entropy, Variation_information, Precision,Recall,F_measure,Fowlkes_mallows_index,Connectivity,Dunn, Silhouette.

Value

Return a list with both the internal and external evaluation of the grouping.

laperez/Clustering documentation built on June 25, 2022, 5:48 p.m.