evaluate_validation_external_by_metrics: Evaluate external validations by algorithm.

Description Usage Arguments Details Value Examples

View source: R/app.R

Description

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

Usage

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Arguments

df

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

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 variables and measures of dissimilarity.

Value

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

Examples

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result = clustering(
               df = cluster::agriculture,
               min = 4,
               max = 5,
               algorithm='kmeans_arma',
               metrics=c("precision"),
               variables = TRUE
         )

evaluate_validation_external_by_metrics(result)

## Not run: 
evaluate_validation_external_by_metrics(result$result)

## End(Not run)

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