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Multi-class classification research benchmarks – Page 8 · SOTA2 Research

Multi-class classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Edema Severity (test)

0.807AUC

5

Feb 26, 2026

96.98F1-score

4

Apr 15, 2026

UNSW-NB15 (test)

95.12F1 Score

4

Apr 15, 2026

93.15Accuracy

4

Mar 13, 2026

Annealing (test)

86.6Macro F1 Score

4

Mar 13, 2026

83.5Macro F1

4

Mar 13, 2026

96.3Macro F1 Score

4

Mar 13, 2026

Lymphography (test)

61Macro F1 Score

4

Mar 13, 2026

94.3Macro F1

4

Mar 13, 2026

33 Tabular Datasets Multi-class

RocketStack-Level10 (Periodic Attention (Rand-λ = 0.05))

94.82Accuracy

4

Mar 4, 2026

0.548MCC

4

Feb 26, 2026

ADNI AD vs NC vs EMCI vs LMCI

Multi-Modal Hypergraph Diffusion Network

18.31Error Rate

4

Feb 26, 2026

ADNI AD vs NC vs MCI

Multi-Modal Hypergraph Diffusion Network

0.163Error Rate

4

Feb 26, 2026

81.5Accuracy

4

Feb 27, 2026

64.9Accuracy

4

Feb 27, 2026

86.1Accuracy

4

Feb 27, 2026

Content Rating Descriptors (CRD-9)

Gemini-2.5-Flash

83.94Mild Precision

3

May 21, 2026

Gradient Boosting

99.51Accuracy (Fridge)

3

Apr 14, 2026

Tsetlin Machine

90.7Accuracy

3

Apr 6, 2026

CICIoT 2023 (test)

98.68Accuracy

3

Mar 18, 2026

88.1Macro F1-score

3

Mar 13, 2026

48.43Accuracy

3

Feb 26, 2026

49.55Accuracy

3

Feb 26, 2026

LT-CIFAR10 imb. 100 (test)

0.267Error Rate @ 80% TPR

3

Feb 26, 2026

56.61Accuracy

2

Feb 27, 2026

Page 8 of 9

Popular datasets

CIFAR OpenML EBES ADNI CIFAR100

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