Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models.

Siam AM, Bhowmik P, Uddin MP

DOI: 10.1371/journal.pone.0326975
Published: 2025
Container: PloS one
Publisher: Not recorded
Open access: yes

Credibility signals

limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0326975,
  title = {Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models.},
  author = {Siam AM and Bhowmik P and Uddin MP},
  year = {2025},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0326975},
  url = {https://doi.org/10.1371/journal.pone.0326975}
}

RIS

TY  - JOUR
TI  - Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models.
AU  - Siam AM
AU  - Bhowmik P
AU  - Uddin MP
PY  - 2025
JO  - PloS one
DO  - 10.1371/journal.pone.0326975
UR  - https://doi.org/10.1371/journal.pone.0326975
ER  -

APA

AM, S., P, B., & MP, U. (2025). Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models.. PloS one. https://doi.org/10.1371/journal.pone.0326975

Source records

pubmed · retrieved 2026-09-25T06:42:11.592Z