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DEnsity-BAsed CLustering

Project description

DeBaCl is an open-source Python library for DEnsity-BAsed CLustering with level set trees.

Level set trees are a statistically-principled way to represent the topology of a probability density function. This representation is particularly useful for several core tasks in statistics:

  • clustering, especially for data with multi-scale clustering behavior
  • describing data topology
  • exploratory data analysis
  • data visualization
  • anomaly detection

DeBaCl is a Python implementation of the Level Set Tree method, with an emphasis on computational speed, algorithmic simplicity, and extensibility. The code is available at:

https://github.com/CoAxLab/DeBaCl

and the API documentation is at:

https://debacl.readthedocs.org/en/v1.1/

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