Metadata-Version: 2.1
Name: enhanced_adaptive_dbscan
Version: 0.1.0
Summary: An Enhanced Adaptive DBSCAN clustering algorithm for semiconductor wafer defects.
Home-page: https://github.com/kennedym-ds/enhanced_adaptive_dbscan
Author: Michael Kennedy
Author-email: michael.patrick.kennedy@outlook.ie
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: License
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: plotly
Requires-Dist: joblib
Requires-Dist: pandas
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: sphinx; extra == "dev"
Requires-Dist: wheel; extra == "dev"

# Enhanced Adaptive DBSCAN

An Enhanced Adaptive DBSCAN clustering algorithm tailored for semiconductor wafer defect analysis.

## Features

- **Adaptive Parameter Selection:** Adjusts Îµ and MinPts based on local density.
- **Stability-Based Cluster Selection:** Retains only robust and persistent clusters.
- **Dynamic Cluster Centers:** Maintains up-to-date cluster centroids.
- **Partial Re-Clustering:** Efficiently updates affected clusters with new data points.
- **Incremental Clustering:** Handles streaming data seamlessly.
- **Interactive Visualization:** Utilizes Plotly for dynamic cluster plots.
- **Comprehensive Logging:** Tracks the algorithm's progress and decisions.

## Installation

```bash
pip install enhanced_adaptive_dbscan
