evaluate_validation_external_by_metrics: Evaluate external validations by algorithm.

In laperez/Clustering: Techniques for Evaluating Clustering

Evaluate external validations by algorithm.

Description

Method that calculates which algorithm behaves best for the datasets provided.

Usage

evaluate_validation_external_by_metrics(df)

Arguments

df	data matrix or data frame with the result of running the clustering algorithm.

Details

It groups the results of the execution by algorithms.

Value

A data.frame with all the algorithms that obtain the best results regardless of the dissimilarity measure used.

Examples

result = Clustering::clustering(
               df = cluster::agriculture,
               min = 4,
               max = 4,
               algorithm='kmeans_arma',
               metrics=c("Precision")
         )

Clustering::evaluate_validation_external_by_metrics(result)

laperez/Clustering documentation built on April 23, 2024, 3:41 a.m.