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Toolbox for Machine Learning using Topological Data Analysis.

Project description

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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)
  • python-igraph (>= 0.7.1.post6)
  • plotly (>= 4.4.1)
  • matplotlib (>= 3.1.2)

To run the examples, jupyter is 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

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

The CMake and Boost dependencies can be installed in using Anaconda as follows:

conda install -c anaconda cmake
conda install -c anaconda boost
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.

Project details


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