PreDeCon - An Implementation in Python, Compatible With Scikit-Learn
Project description
PreDeCon
This repository is not associated with the original authors of [Boehm,2004].
About
Subspace Preference Weighted Density Connected Clustering (PreDeCon) [Boehm,2004] can be seen as a modification to the famous DBSCAN [Ester,1996] that addresses problems which arise in high-dimensional spaces.
Installation
Install with pip
.
From PyPI
$ pip install predecon-exioreed
Alternatively, from source
$ pip install git+https://github.com/exioReed/PreDeCon@master#egg=PreDeCon-exioreed
or
$ git clone https://github.com/exioReed/PreDeCon.git
$ cd PreDeCon
$ pip install .
References
[Boehm,2004]
Boehm, C. et al., "Density Connected Clustering with Local Subspace Preferences".
In: Proceedings of the 4th IEEE Internation Conference on Data Mining (ICDM),
Brighton, UK, 2004.
[Ester,1996]
Ester, M. et al., "A Density-Based Algorithm for Discovering Clusters in Large
Spatial Databases with Noise".
In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining,
Portland, OR, 1996.
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