Multi-class Classification on Bayesian Network variable D2 benchmark leaderboard · SOTA2 Research

Multi-class Classification on Bayesian Network variable D2

76.55Macro-F1Diff-Joint

Evaluation Results

Method	Links
Diff-Joint2026.06		76.55	95.49	72.57	90
Diff-Joint2026.06		75.54	94.81	71.42	89.38
Diff-Joint2026.06		75.44	95.26	71.23	89.72
Diff-Joint2026.06		61.11	94.77	53.94	86.15
Mean/Mode2026.06		46.5	73.38	40.21	72.65
DiffPuter2026.06		46.47	74.72	40.17	72.65
DiffPuter2026.06		46.38	73.92	40.07	72.62
DiffPuter2026.06		45.97	74.01	39.58	72.52
missForest2026.06		45.7	72.12	39.24	72.39
CMAE2026.06		45.25	72.42	37.12	71.85
DiffPuter2026.06		43.23	74.3	36.11	72.18
CMAE2026.06		42.1	72.79	33.48	70.72
CMAE2026.06		40.82	70.39	32.02	70.1
Mean/Mode2026.06		40.03	69.54	32.47	71.25
missForest2026.06		39.59	68.44	31.97	70.83
CMAE2026.06		38.85	69.95	29.62	69.08
Mean/Mode2026.06		37.12	68.25	28.97	70.75
missForest2026.06		36.54	66.04	28.36	69.9
Mean/Mode2026.06		35.11	70.68	26.49	70.89
missForest2026.06		33.97	68.49	25.22	69.94