apclusterK_manhattan: Method that runs the apclusterK algorithm using the manhattan...

Description Usage Arguments Value

View source: R/apcluster.R

Description

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

Usage

1
apclusterK_manhattan(dt, clusters, columnClass, metric)

Arguments

dt

matrix or data frame with the set of values to be applied to the algorithm.

clusters

is an integer that indexes the number of clusters we want to create.

columnClass

is an integer with the number of columns, for example if a dataset has five column, we can select column four to calculate alidation.

metric

is 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

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


laperez/Clustering documentation built on Aug. 1, 2020, 12:54 p.m.