Metadata-Version: 2.1
Name: deltric
Version: 0.2.0
Summary: Delaunay Triangulation Clustering - density-robust clustering with built-in outlier detection
Home-page: https://github.com/TomasJavurek/deltric
Author: TomasJavurek
License: MIT
Keywords: clustering,outlier-detection,anomaly-detection,delaunay-triangulation,unsupervised-learning
Requires-Python: >=3.8
Requires-Dist: numpy>=1.20
Requires-Dist: scikit-learn>=1.0
Requires-Dist: scipy>=1.7
Requires-Dist: networkx>=2.6
Requires-Dist: umap-learn>=0.5
Requires-Dist: statsmodels>=0.13
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown

# DelTriC - Delaunay Triangulation Clustering

**Density-robust clustering with built-in outlier detection.**

## Quick Start

    from deltric import DelTriC
    model = DelTriC()
    labels = model.fit_predict(X)

## Features
- No need to specify k
- Arbitrary cluster shapes
- Built-in outlier detection
- Auto-param mode
- scikit-learn compatible
