HiPart: Hierarchical Divisive Clustering Toolbox

TL;DR

HiPart is an open-source Python library offering efficient, interpretable divisive hierarchical clustering with interactive visualization, designed for big data applications and easy integration.

Contribution

The paper introduces HiPart, a new Python package that implements efficient, interpretable divisive hierarchical clustering with interactive visualization capabilities.

Findings

Supports large-scale data clustering efficiently

Provides interactive visualization for clustering steps

Open-source with easy-to-use interface

Abstract

This paper presents the HiPart package, an open-source native python library that provides efficient and interpret-able implementations of divisive hierarchical clustering algorithms. HiPart supports interactive visualizations for the manipulation of the execution steps allowing the direct intervention of the clustering outcome. This package is highly suited for Big Data applications as the focus has been given to the computational efficiency of the implemented clustering methodologies. The dependencies used are either Python build-in packages or highly maintained stable external packages. The software is provided under the MIT license. The package's source code and documentation can be found at https://github.com/panagiotisanagnostou/HiPart.