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:
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size debacl-1.1-py2-none-any.whl (25.6 kB) | File type Wheel | Python version py2 | Upload date | Hashes View |
| Filename, size debacl-1.1.tar.gz (22.5 kB) | File type Source | Python version None | Upload date | Hashes View |