execute_datasets: Evaluation clustering algorithm.

Description Usage Arguments Value

View source: R/app.R

Description

Method of performing information processing

Usage

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execute_datasets(
  path,
  df,
  packages,
  algorithm,
  cluster_min,
  cluster_max,
  metrics,
  variables
)

Arguments

path

path where the datasets are located.

df

data matrix or data frame, or dissimilarity matrix, depending on the value of the argument.

packages

array defining the clustering package. The seven packages implemented are: cluster, ClusterR, advclust, amap, apcluster, gama, pvclust. By default runs all packages.

algorithm

array with the algorithms that implement the package. The algorithms implemented are: fuzzy_cm,fuzzy_gg,fuzzy_gk,hclust,apclusterK,agnes,clara,daisy,diana,fanny,mona,pam,gmm,kmeans_arma,kmeans_rcpp,mini_kmeans,gama,pvclust.

cluster_min

minimum number of clusters. at least one must be.

cluster_max

maximum number of clusters. cluster_max must be greater or equal cluster_min.

metrics

array defining the metrics avalaible in the package. The night metrics implemented are: entropy, variation_information,precision,recall,f_measure,fowlkes_mallows_index,connectivity,dunn,silhouette.

variables

accepts Boolean values. If true as a result it shows the variable that behaves best otherwise it shows the value of the executed metric.

Value

returns a matrix with the result of running all the metrics of the algorithms contained in the packages we indicated.


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