evaluate_validation_internal_by_metrics function

Evaluate internal validations by algorithm.

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

evaluate_validation_internal_by_metrics(df)

Arguments

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

Returns

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

Details

It groups the results of the execution by algorithms.

Examples

result = Clustering::clustering(
               df = cluster::agriculture,
               min = 4,
               max = 5,
               algorithm='kmeans_rcpp',
               metrics=c("Recall","Silhouette")
         )

Clustering::evaluate_validation_internal_by_metrics(result)

Clustering::evaluate_validation_internal_by_metrics(result$result)