Clustering (version 1.7)

evaluate_validation_internal_by_metrics: Evaluate internal validations by algorithm.

Description

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

Usage

evaluate_validation_internal_by_metrics(df)

Arguments

df

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

Value

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

Details

The operation of this method is to determine which algorithm has better behavior regardless of the measure of dissimilarity calculated, so we can determine which algorithm returns better results from the attributes and measures of dissimilarity.

Examples

# NOT RUN {
result = clustering(
               df = cluster::agriculture,
               min = 4,
               max = 5,
               algorithm='kmeans_rcpp',
               metrics=c("silhouette"),
               attributes = TRUE
         )

evaluate_validation_internal_by_metrics(result)

# }
# NOT RUN {
evaluate_validation_internal_by_metrics(result$result)
# }
# NOT RUN {
# }