HiPart: Hierarchical Divisive Clustering Toolbox
This is an incremental contribution providing a new software tool for data scientists and researchers needing scalable hierarchical clustering.
The authors introduced HiPart, an open-source Python library for efficient and interpretable divisive hierarchical clustering, designed for Big Data applications with a focus on computational efficiency.
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.