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Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data
Research article (JAMIA Open, 2023) · cited 30× · AI/ML
Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data
Summary
Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data is a scholarly article[1].
Key Facts
Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data. Retrieved May 24, 2026, from https://4ort.xyz/entity/implications-of-resampling-data-to-address-the-class-imbalance-problem-ircip-an-evaluation-of-impact-on-performance-betw
MLA“Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/implications-of-resampling-data-to-address-the-class-imbalance-problem-ircip-an-evaluation-of-impact-on-performance-betw.
BibTeX@misc{4ortxyz_implications-of-resampling-data-to-address-the-class-imbalance-problem-ircip-an-evaluation-of-impact-on-performance-betw_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data}}, year = {2026}, url = {https://4ort.xyz/entity/implications-of-resampling-data-to-address-the-class-imbalance-problem-ircip-an-evaluation-of-impact-on-performance-betw}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data — https://4ort.xyz/entity/implications-of-resampling-data-to-address-the-class-imbalance-problem-ircip-an-evaluation-of-impact-on-performance-betw (retrieved 2026-05-24)
