Abstract: Topological Data Analysis is a recent and fast growing field providing a set of new topological and geometric tools to infer relevant features for possibly complex data. This paper is a brief introduction, through a few selected topics, to basic fundamental and practical aspects of \tda\ for non experts.
| Subjects: | Statistics Theory (math.ST) ; Machine Learning (cs.LG); Algebraic Topology (math.AT); Machine Learning (stat.ML) |
| Cite as: | arXiv:1710.04019 [math.ST] |
| (or arXiv:1710.04019v2 [math.ST] for this version) | |
| https://doi.org/10.48550/arXiv.1710.04019 |
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arXiv-issued DOI via DataCiteFrom: Bertrand Michel [view email] [via CCSD proxy]
[v1] Wed, 11 Oct 2017 11:53:32 UTC (1,301 KB)
[v2] Thu, 25 Feb 2021 08:31:59 UTC (4,701 KB)
View a PDF of the paper titled An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists, by Fr\'ed\'eric Chazal (1) and 2 other authors