Weight-based Subspace Clustering
Project description
PySubCMedians
Authors: Sergio Peignier, Christophe Rigotti, Anthony Rossi and Guillaume Beslon
Python implementation of the SubCMedians algorithm. SubCMedians is a Subspace Clustering algorithm that extends the K-medians paradigm. SubCMedians is a simple hill climbing algorithm based on stochastic weighted local exploration steps. This median based algorithm exhibits satisfactory quality clusters when compared to well-established paradigms, while medians have still their own interests depending on the user application (robustness to noise/outliers and location optimality). Detailled description available in the paper "Weight-based search to find clusters around medians in subspaces" presented in the ACM SAC conference 2018.
Installation
Dependencies :
- numpy
- pandas
- seaborn
- scikit-learn
- scipy
- tqdm
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