K Means Python Packages

k-means-constrained

K-Means clustering - constrained with minimum and maximum cluster size. Documentation: https://joshlk.github.io/k-means-constrained

ckmeans

A Python package for fast 1D clustering using a Rust binary. Prefer ckmeans to Jenks.

polyvoice

CPU speaker diarization with native INT8 kernels. Rust, CLI, Python and C interfaces; no ONNX Runtime in the core.

diffsptk

A differentiable version of SPTK

superkmeans

⚡ Super fast clustering for high-dimensional vectors on CPUs (x86, ARM) and GPUs — for Python and C++. Faster clustering of vector embeddings than FAISS

markov-kmeans

Early stopping for K-means: stop when only boundary points still switch clusters, and settle them from their own label history. Shorter runs, uncertainty flags, soft memberships. Exact Lloyd, mini-batch and EMA (constant-step) training. scikit-learn compatible.

pyckmeans

Consensus and WECR K-Means clustering.

compsil

CompSil: Composite Silhouette for Cluster-Count Selection

imgrit

A tiny image processing library with k-means and Voronoi diagram.

som-multimodal-datareduction

Self-organizing-map (SOM) reduction of multimodal materials data (nanomechanics, Raman, fracture): the packaged analysis behind Renteria et al., JMBBM 2022.

ml-python

Easy to use high level python library for popular machine learning algorithms. Has in-built support for graphing and optimizers based in C++.

spherecluster

Clustering routines for the unit sphere

dovalens

CLI for dataset profiling, statistics, clustering/anomaly detection, and drift (KS); generates a single HTML report from a CSV.

synloc

A Python Package to Create Synthetic Tabular Data

composite-silhouette

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

ballot

High-performance Python package for balanced k-means clustering using optimal transport and entropic regularization

mp-kmeans

Real mixed-precision k-means