K Means Clustering Python Packages

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.

compsil

CompSil: Composite Silhouette for Cluster-Count Selection

kmeans-tjdwill

An implementation of k-means clustering that maintains data association.

ztlearn

zeta-lean: minimalistic python machine learning library built on top of numpy and matplotlib

pocs-based-clustering

POCS-based Clustering Algorithm

customerprofile

An easy-to-use package for customer segmentation using Python.

connor-nlp

Organize and classify files based on their content using NLP