Machine learning performance for a small dataset: random oversampling improves data imbalances and fairness.
- DOI
- 10.1186/s12874-026-02779-3
- Published
- 2026 Feb 4
- Container
- BMC medical research methodology
- 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.
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Cite this work
BibTeX
@article{allodium:10.1186/s12874-026-02779-3,
title = {Machine learning performance for a small dataset: random oversampling improves data imbalances and fairness.},
author = {Wang L and Shi E and Meyers B and Vlachos P and Tcheng J and Denardo S},
year = {2026},
journal = {BMC medical research methodology},
doi = {10.1186/s12874-026-02779-3},
url = {https://doi.org/10.1186/s12874-026-02779-3}
}RIS
TY - JOUR TI - Machine learning performance for a small dataset: random oversampling improves data imbalances and fairness. AU - Wang L AU - Shi E AU - Meyers B AU - Vlachos P AU - Tcheng J AU - Denardo S PY - 2026 JO - BMC medical research methodology DO - 10.1186/s12874-026-02779-3 UR - https://doi.org/10.1186/s12874-026-02779-3 ER -
APA
L, W., E, S., B, M., P, V., J, T., & S, D. (2026). Machine learning performance for a small dataset: random oversampling improves data imbalances and fairness.. BMC medical research methodology. https://doi.org/10.1186/s12874-026-02779-3
Source records
- pubmed · retrieved 2026-09-25T15:19:47.489Z