giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data ExplorationDownload PDF

Published: 31 Oct 2020, Last Modified: 29 Aug 2024TDA & Beyond 2020 SpotlightReaders: Everyone
Keywords: Topological Data Analysis, Machine Learning, Data Exploration, Persistent Homology, Mapper
TL;DR: 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.
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
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Poster: pdf
Community Implementations: [![CatalyzeX](/images/catalyzex_icon.svg) 4 code implementations](https://www.catalyzex.com/paper/giotto-tda-a-topological-data-analysis/code)
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