Giotto-Tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration
Abstract
We introduce giotto-tda, a Python library that integrates high-performance topological data analysis with machine learning via a scikit-learn-compatible API and state-of-the-art C++ implementations. The library's ability to handle various types of data is rooted in a wide range of preprocessing techniques, and its strong focus on data exploration and interpretability is aided by an intuitive plotting API. Source code, binaries, examples, and documentation can be found at https://github.com/giotto-ai/giotto-tda
Cite
Text
Tauzin et al. "Giotto-Tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration." NeurIPS 2020 Workshops: TDA_and_Beyond, 2020.Markdown
[Tauzin et al. "Giotto-Tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration." NeurIPS 2020 Workshops: TDA_and_Beyond, 2020.](https://mlanthology.org/neuripsw/2020/tauzin2020neuripsw-giottotda/)BibTeX
@inproceedings{tauzin2020neuripsw-giottotda,
title = {{Giotto-Tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration}},
author = {Tauzin, Guillaume and Lupo, Umberto and Tunstall, Lewis and Perez, Julian Burella and Caorsi, Matteo and Reise, Wojciech and Medina-Mardones, Anibal Maximiliano and Dassatti, Alberto and Hess, Kathryn},
booktitle = {NeurIPS 2020 Workshops: TDA_and_Beyond},
year = {2020},
url = {https://mlanthology.org/neuripsw/2020/tauzin2020neuripsw-giottotda/}
}