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DADApy: Distance-based analysis of data-manifolds in Python

Glielmo, Aldo
•
Macocco, Iuri
•
Doimo, Diego
altro
Laio, Alessandro
2022
  • journal article

Periodico
PATTERNS
Abstract
DADApy is a Python software package for analyzing and characterizing high-dimensional data manifolds. It provides methods for estimating the intrinsic dimension and the probability density, for performing density-based clustering, and for comparing different distance metrics. We review the main functionalities of the package and exemplify its usage in a synthetic dataset and in a real-world application. DADApy is freely available under the open-source Apache 2.0 license.
DOI
10.1016/j.patter.2022.100589
WOS
WOS:000898561500009
Archivio
https://hdl.handle.net/11368/3034884
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85139846747
https://www.sciencedirect.com/science/article/pii/S2666389922002070
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by/4.0/
FVG url
https://arts.units.it/bitstream/11368/3034884/1/1-s2.0-S2666389922002070-main.pdf
Soggetti
  • density estimation

  • density-based cluster...

  • feature selection

  • intrinsic dimension

  • manifold analysi

  • metric learning

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