Kmeans Python Packages

kmeans1d

A Python package for optimal 1D k-means clustering.

55K 55 9

neurocaps

Co-activation Patterns (CAPs) Python package

7K 18 5

gap-stat

Python implementation of the gap statistic with optional Rust optimizations.

3K 229 50

clumppy

Clustering algorithms

2K 0 0

pycave

Traditional Machine Learning Models for Large-Scale Datasets in PyTorch.

2K 129 13

pdc-dp-means

"Revisiting DP-Means: Fast Scalable Algorithms via Parallelism and Delayed Cluster Creation" [Dinari and Freifeld, UAI 2022]

1K 21 4

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

991 61 4

colorz

Color scheme generator.

971 185 11

libkmcuda

Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

691 840 147

allmeans

Automatic topic modelling using minimal external input and computational resources

546 2 0

metacluster

MetaCluster: An Open-Source Python Library for Metaheuristic-based Clustering Problems

526 17 4

rectokens

A tokenizer library for sequential recommendation systems

521 4 0

raster2poly

Classify rasters (KMeans, Random Forest, DN rules) and vectorise to polygons.

490 0 0

constrainedkmeans

Constrained KMeans algorithm.

356 8 0

optimalcluster

OptimalCluster is the Python implementation of various algorithms to find the optimal number of clusters. The algorithms include elbow, elbow-k_factor, silhouette, gap statistics, gap statistics with standard error, and gap statistics without log. Various types of visualizations are also supported.

313 2 0

hgpack

Source code of HG-means clustering, from "HG-means: A scalable hybrid genetic algorithm for minimum sum-of-squares clustering". (Gribel and Vidal, 2019)

304 10 3