Internal measures for cluster validation (Comparisons' comparability for transitivity evaluation)

internal_measures_plot currently prepares the table with the results of the average silhouette width for a range of clusters, and visualises the results using a profile plot.

Usage

internal_measures_plot(
  input,
  optimal_link,
  label_size = 4,
  axis_title_size = 14,
  axis_text_size = 14
)

Arguments

input: An object of 'dist' class. It is a lower off-diagonal matrix with the dissimilarities of all pairs of comparisons.
optimal_link: A character string with values "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", or "centroid" for the optimal linkage method, corresponding to the highest cophenetic correlation coefficient value.
label_size: A positive integer for the font size of labels in the profile plot with the average silhouette width per candidate cluster. label_size determines the size argument found in the geom's aesthetic properties in the R-package ggplot2.
axis_title_size: A positive integer for the font size of axis title in the profile plot with the average silhouette width per candidate cluster. axis_title_size determines the axis.title argument found in the theme's properties in the R-package ggplot2.
axis_text_size: A positive integer for the font size of axis text in the profile plot with the average silhouette width per candidate cluster. axis_text_size determines the axis.text argument found in the theme's properties in the R-package ggplot2.

Value

internal_measures_plot currently returns the following list of elements:

Table_internal_measures: A data-frame of the average silhouette width for a range of 2 to P-1 clusters, with P being the number of trials
Internal_measures_panel: A profile plot on the average silhouette width for a range of 2 to P-1 clusters, with P being the number of trials The candidate optimal number of clusters is indicated with a red point directly on the line.

Details

internal_measures_plot also calls the function comp_clustering to define the argument optimal_link to create the silhouette plot for the selected number of clusters.

internal_measures_plot calls the silhouette function in the R-package cluster to obtain the results on average silhouette for each candidate cluster.

internal_measures_plot is integrated in the function comp_clustering.

References

Handl J, Knowles J, Kell DB. Computational cluster validation in post-genomic data analysis. Biometrics 2005;21(15):3201–120. doi: 10.1093/bioinformatics/bti517

Rousseeuw PJ. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 1987;20:53–65.

Author

Loukia M. Spineli