hclust_genetic_solution {emcAdr}R Documentation

Clustering of the solutions of the genetic algorithm using the hclust algorithm

Description

Clustering of the solutions of the genetic algorithm using the hclust algorithm

Usage

hclust_genetic_solution(
  genetic_results,
  ATCtree,
  dist.normalize = TRUE,
  method = "complete"
)

Arguments

genetic_results

The return value of the genetic algorithm

ATCtree

ATC tree with upper bound of the DFS

dist.normalize

Do we normalize the distance (so it bellongs to [0;1])

method

(from hclust function) the agglomeration method to be used. This should be (an unambiguous abbreviation of) one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).

Value

the hierarchical clustering of the results of the genetic algorithm

Examples


data("ATC_Tree_UpperBound_2024")
data("FAERS_myopathy")

results = GeneticAlgorithm(epochs = 10, nbIndividuals = 10, 
            ATCtree = ATC_Tree_UpperBound_2024,
            observations = FAERS_myopathy)

hclust_genetic_solution(genetic_results = results,
                 ATCtree = ATC_Tree_UpperBound_2024)


[Package emcAdr version 1.2 Index]