Toolbox for Machine Learning using Topological Data Analysis.
Project description
giotto-learn
giotto-learn is a high performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the Apache 2.0 license. It is part of the Giotto open-source project.
Website: https://giotto.ai
Project genesis
giotto-learn is the result of a collaborative effort between L2F SA, the Laboratory for Topology and Neuroscience at EPFL, and the Institute of Reconfigurable & Embedded Digital Systems (REDS) of HEIG-VD.
Installation
Dependencies
giotto-learn requires:
Python (>= 3.5)
scikit-learn (>= 0.21.3)
NumPy (>= 1.17.0)
SciPy (>= 0.17.0)
joblib (>= 0.11)
For running the examples jupyter, matplotlib and plotly are required.
User installation
If you already have a working installation of numpy and scipy, the easiest way to install giotto-learn is using pip
pip install -U giotto-learn
Documentation
HTML documentation (stable release): https://docs.giotto.ai
Contributing
We welcome new contributors of all experience levels. The Giotto community goals are to be helpful, welcoming, and effective. To learn more about making a contribution to giotto-learn, please see the CONTRIBUTING.rst file.
Developer installation
C++ dependencies:
C++14 compatible compiler
CMake >= 3.9
Boost >= 1.56
Source code
You can check the latest sources with the command:
git clone https://github.com/giotto-ai/giotto-learn.git
To install:
cd giotto-learn
pip install -e .
From there any change in the library files will be immediately available on your machine.
Testing
After installation, you can launch the test suite from outside the source directory:
pytest giotto
Changelog
See the RELEASE.rst file for a history of notable changes to giotto-learn.
Important links
Official source code repo: https://github.com/giotto-ai/giotto-learn
Download releases: https://pypi.org/project/giotto-learn/
Issue tracker: https://github.com/giotto-ai/giotto-learn/issues
Contacts:
Project details
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