Hierarchical Cluster Comparison

Hierarchical Cluster Comparison by E. B. Fowlkes and C. L. Mallows (1983)

You are now following this Submission

The zip file contains three functions written for the paper "Comparative adenine dinucleotide phosphate
(NADPH)-diaphorase histochemistry in amphibian brain: a cluster analysis" by Claudia Pinelli, Rakesh K. Rastogi, Anna Scandurra, Arun G. Jadhao, Massimo Aria, Biagio D’Aniello, accepted on Journal of Comparative Neurology (2014).

The functions are:

- Cluster_comparison.m that calculates the B measure proposed by E. B. Fowlkes and C. L. Mallows (1983) to compare the results of two different hierarchical clustering performed on the same dataset;
- Bootstrap_compare_cluster.m that estimates the 95% bootstrap confidence interval of B measure;
- PermTest_cluster_compare.m that performs a permutation test on B measure.
Null Hypothesis of the test is: The two hierarchical partitions (C_A and C_B) are completely uncorrelated, in other word, are completely different.
Alternative Hypothesis is: The two hierarchical partitions are correlated, in other word, have significant similarity.
C_A represents a well-known partition of objects provided by theoretical assumptions.
C_B represents a hierarchical partition obtained by a statistical analysis on a real dataset.

Cite As

Massimo Aria (2026). Hierarchical Cluster Comparison (https://www.mathworks.com/matlabcentral/fileexchange/45222-hierarchical-cluster-comparison), MATLAB Central File Exchange. Retrieved .

Categories

Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.0.0.0