Search 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.

pyckmeans

Consensus and WECR K-Means clustering.

diffsptk

A differentiable version of SPTK

spherecluster

Clustering routines for the unit sphere

superkmeans

⚡ Super fast clustering for high-dimensional vectors on CPUs (x86, ARM) and GPUs — for Python and C++. 100x faster clustering of vector embeddings than FAISS

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++.

synloc

A Python package to create synthetic data from locally estimated distributions

dovalens

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

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