MultiDendrograms: Variable-Group Agglomerative Hierarchical Clusterings

TL;DR

MultiDendrograms is a Java application that computes hierarchical clusterings using a variable-group algorithm to address non-uniqueness issues caused by tied distances, enabling more consistent dendrograms.

Contribution

It introduces a variable-group algorithm for agglomerative clustering that handles tie situations by grouping multiple clusters simultaneously, improving clustering consistency.

Findings

Addresses non-uniqueness in hierarchical clustering due to tied distances.

Implements a variable-group algorithm for more consistent dendrograms.

Provides a Java tool for practical hierarchical clustering applications.

Abstract

MultiDendrograms is a Java-written application that computes agglomerative hierarchical clusterings of data. Starting from a distances (or weights) matrix, MultiDendrograms is able to calculate its dendrograms using the most common agglomerative hierarchical clustering methods. The application implements a variable-group algorithm that solves the non-uniqueness problem found in the standard pair-group algorithm. This problem arises when two or more minimum distances between different clusters are equal during the agglomerative process, because then different output clusterings are possible depending on the criterion used to break ties between distances. MultiDendrograms solves this problem implementing a variable-group algorithm that groups more than two clusters at the same time when ties occur.