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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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