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:
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