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Classification research benchmarks – Page 45 · SOTA2 Research

Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

bupa 25% label noise (test)

71.6Accuracy

14

Mar 9, 2026

blood 25% label noise (test)

79.3Accuracy

14

Mar 9, 2026

australian 25% label noise (test)

87.5Accuracy

14

Mar 9, 2026

appendicitis 25% label noise (test)

91.4Accuracy

14

Mar 9, 2026

PPG Classification Benchmark Suite

99.94Stress Accuracy

14

Feb 26, 2026

TabPFN-Proxy-Hybrid

100ROC AUC

14

Mar 31, 2026

1ROC AUC

14

Mar 31, 2026

89.8Accuracy

14

May 8, 2026

96.97Accuracy

14

Feb 26, 2026

82.8AUC

14

Feb 26, 2026

ACSIncome state AZ

81.6Avg Acc

14

Feb 26, 2026

ACSEmployment CT (test)

79.3AV.ACC

14

Feb 26, 2026

ACSIncome state RI (test)

79.2Avg Accuracy

14

Feb 26, 2026

Finetuned BioBERT_CAMLM

69.7AUROC

14

Feb 26, 2026

41Power-Seeking

14

Feb 26, 2026

Office-Home-LDS beta=0.1 (test)

79.01Accuracy

14

Feb 26, 2026

98.3Top-1 Accuracy

14

Mar 4, 2026

medium-sized classification datasets

78.58Accuracy

14

Feb 26, 2026

Genomic Benchmarks

96.3Coding vs Intergenomic Classification

14

Jun 4, 2026

47.9Type-I Accuracy

14

Feb 26, 2026

Fine-grained classification benchmarks (Food-101, CIFAR-10, CIFAR-100, SUN397, Stanford Cars, FGVC Aircraft, Pascal VOC 2007, DTD, Oxford-IIIT Pets, Caltech-101, Oxford Flowers 102, CUB-200-2011)

83.4Accuracy (Food-101)

14

Feb 26, 2026

25.2Avg Expected Loss

14

Feb 26, 2026

8Avg Loss

14

Feb 26, 2026

CIFAR-10 Imbalanced

11.7Average Expected Loss

14

Feb 26, 2026

31.1Average Expected Loss

14

Feb 26, 2026

Page 45 of 202

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CIFAR MNIST Adult ImageNet Wine

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