Cluster Analysis Python Packages

hdbscan

A high performance implementation of HDBSCAN clustering.

sequenzo

A fast, scalable, and intuitive Python package in sequence analysis.

genieclust

Genie: Fast and Robust Hierarchical Clustering

bf44-hdbscan-0844

A high performance implementation of HDBSCAN clustering.

quitefastmst

quitefastmst: Euclidean and Mutual Reachability Minimum Spanning Trees

pyclustertend

A python package to assess cluster tendency

hdbscan-314

A high performance implementation of HDBSCAN clustering.

psgg-hdbscan-0844

A high performance implementation of HDBSCAN clustering.

lumbermark

Lumbermark: Resistant Clustering via Chopping Up Mutual Reachability Minimum Spanning Trees

s-dbw

S_Dbw validity index. Adapted for DBSCAN (and similar)

persistable-clustering

density-based clustering for exploratory data analysis based on multi-parameter persistence

hopkins-statistic

A Python package for computing the Hopkins statistic to assess clustering tendency.

finchpy

A Python implementation of "FINCH Clustering Algorithm (CVPR 2019)"

trcc

Density-peak clustering with path-density mutual-reachability merging. Sub-quadratic O(n log n) via a C++ pybind11/nanoflann kd-tree. 30× speedup at n=50k.

clustering-benchmarks

A Framework for Benchmarking Clustering Algorithms

gpmix

GPmix is an ensemble clustering algorithm for functional data via random projections.

clusterking

Cluster sets of histograms/curves, in particular kinematic distributions in high energy physics.

cake-ensemble

CAKE: Confidence in Assignments via K-partition Ensembles

bambird

Unsupervised classification to improve the quality of a bird song recording dataset. https://doi.org/10.1016/j.ecoinf.2022.101952

edtools

Collection of tools for automated processing and clustering of electron diffraction data.

sil-score

Exact and approximate silhouette scoring with micro, macro, and weighted cluster averages.

extclustval

A lightweight Python package for external clustering validation metrics.

composite-silhouette

A clustering evaluation framework that combines micro- and macro-averaged silhouette scores into a composite metric using statistical weighting.

cluster-ss

Improving Clustering Problem Analysis with a simple Silhouette Metric Support and Sklearn Estimators Fit