Who Cited It

Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced\n Datasets in Machine Learning

2016 · arXiv (Cornell University) · 1,433 citations · 1 from inside this corpus

Guillaume Lemaître, Fernando Nogueira low, Christos K. Aridas

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced\n Datasets in Machin… (2016)Imbalanced-learn: A Python To…SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Ann… (2018)SMOTE for Learning from Imbal…
1 of 1 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What cites it, inside the corpus

PaperYearCited
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Ann…20182,226

Links

DOI · Open access copy · OpenAlex record

Topics

Imbalanced Data Classification TechniquesComputer Science
Artificial Intelligence in HealthcareHealth Professions
COVID-19 diagnosis using AIMedicine

Is this record sound?

partial

One field of this record is missing or disagrees with another. What is shown below is what the source publishes.

  • supports3 author record(s) attached.
  • weakensNo references are recorded despite 1,433 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:59+00:00.

sha256 59007f057c7dae86…