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Machine learning for quantitative LIBS analysis of aluminum alloys: a comparison of random forest, gradient boosting, and extremely randomized trees — Europe PMC PMID:42120495

Source: Europe PMC (en)
Original: https://europepmc.org/article/MED/42120495
DOI: 10.1038/s41598-[numero omesso]-2
License (as archived): solo-consultazione
Archived: 2026-11-02T11:10:14.288Z
SHA-256 of the archived text: 2e8d09d4823c3126998fcf1f5a4898dfa6ee810a87b7954145b6ee322206944f
Stable URL of this page: https://metraipolis.com/documento/dc_abe8b63bb37d

How to cite

Machine learning for quantitative LIBS analysis of aluminum alloys: a comparison of random forest, gradient boosting, and extremely randomized trees — Europe PMC PMID:42120495 — Europe PMC (en), https://europepmc.org/article/MED/42120495 (solo-consultazione); archived copy: https://metraipolis.com/documento/dc_abe8b63bb37d (Metraipolis archive dc_abe8b63bb37d, sha256 2e8d09d4823c3126998fcf1f5a4898dfa6ee810a87b7954145b6ee322206944f)

BibTeX

@misc{dcabe8b63bb37d,
  title = {Machine learning for quantitative LIBS analysis of aluminum alloys: a comparison of random forest, gradient boosting, and extremely randomized trees — Europe PMC PMID:42120495},
  howpublished = {Europe PMC (en)},
  url = {https://europepmc.org/article/MED/42120495},
  note = {License solo-consultazione; archived copy https://metraipolis.com/documento/dc_abe8b63bb37d; sha256 2e8d09d4823c3126998fcf1f5a4898dfa6ee810a87b7954145b6ee322206944f},
  year = {2026}
}

Archived text

The text is not reproduced here: the archive holds it as solo-consultazione (consultation only, no republication). Read it at the original source: https://europepmc.org/article/MED/42120495. Agents can read the archived copy with the MCP tool read_document.