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Semi-supervised classification research benchmarks – Page 2 · SOTA2 Research

Semi-supervised classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

73.37Accuracy

9

Jun 24, 2026

SLEEPEEG 20% labels

0.62Accuracy

9

Jun 24, 2026

SLEEPEEG 10% labels

61.82Accuracy

9

Jun 24, 2026

SLEEPEEG 5% labels

59.99Accuracy

9

Jun 24, 2026

HARTH 20% labels

88.93Accuracy

9

Jun 24, 2026

HARTH 10% labels

88.16Accuracy

9

Jun 24, 2026

HARTH 5% labels

87.39Accuracy

9

Jun 24, 2026

MNIST 1000 labels

Ladder Networks

0.008Error Rate

8

Feb 26, 2026

STL-10 25 labels per class

91.7Accuracy (Seed 0)

4

Feb 26, 2026

NORB 1000 labels

9.96Error Rate

1

Feb 26, 2026

SVHN 500 labels

—

—Primary metric

0

Feb 26, 2026

MNIST 50 labels

—

—Primary metric

0

Feb 26, 2026

MNIST 20 labels

—

—Primary metric

0

Feb 26, 2026

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