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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/

Release History

Release History

This version
History Node

1.1

History Node

1.0

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0.2.0

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
debacl-1.1-py2-none-any.whl (25.6 kB) Copy SHA256 Checksum SHA256 py2 Wheel Jan 31, 2016
debacl-1.1.tar.gz (22.5 kB) Copy SHA256 Checksum SHA256 Source Jan 31, 2016

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