#dbscan
Python implementation of 'Density Based Spatial Clustering of Applications with Noise'
Setup
python setup.py install
Usage
import dbscan
dbscan.dbscan(m, eps, min_points)
Documentation
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| dbscan.dbscan: (m, eps, min_points)
| Implementation of Density Based Spatial Clustering of Applications with Noise
| See https://en.wikipedia.org/wiki/DBSCAN
|
| scikit-learn probably has a better implementation
| Uses Euclidean Distance as the measure
|
| Inputs:
| m - A matrix whose columns are feature vectors
| eps - Maximum distance two points can be to be regionally related
| min_points - The minimum number of points to make a cluster
|
| Outputs:
| An array with either a cluster id number or dbscan.NOISE (None) for each
| column vector in m.
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