Early Anomaly Detection on PSML multimodal dataset 10% noise (test) benchmark leaderboard · SOTA2 Research

Early Anomaly Detection on PSML multimodal dataset 10% noise (test)

79Accuracy (Acc)MS-SVDD-ω9

Evaluation Results

Method	Links
MS-SVDD-ω92025.02		79	89	68	74	78	11.878	1.488	4.1	38	62	59
MS-SVDD-ω72025.02		78	94	63	72	77	3.867	0.755	3.5	42	58	65
MS-SVDD-ω82025.02		77	93	62	71	76	14.704	0.849	3.5	32	68	65
MS-SVDD-ω32025.02		73	93	52	66	70	5.04	0.509	1.1	64	36	89
MS-SVDD-ω52025.02		72	89	54	66	70	3.125	0.378	1.6	62	38	84
MS-SVDD-ω12025.02		71	95	47	64	67	2.772	0.765	0.9	62	38	91
MS-SVDD-ω42025.02		70	96	44	63	65	3.889	0.509	1.1	66	34	89
MS-SVDD-ω62025.02		70	94	45	63	65	5.989	0.522	1.1	64	36	89
MS-SVDD-ω02025.02		67	88	46	62	64	3.477	0.597	1.3	72	28	87
MS-SVDD-ω22025.02		67	90	45	62	63	4.528	0.773	1.5	76	24	85
CCSSVDD2025.02		53	84	23	52	44	60.956	1.423	2.8	90	10	72
CCSSVDD2025.02		52	92	11	51	32	38.951	0.011	—	100	0	0
OCSVM2025.02		50	100	0	50	0	0.991	0.152	9.2	94	6	8
MS-SVDD-ω92025.02		49	85	12	49	32	8.035	0.027	—	100	0	0
OCSVM2025.02		48	83	14	49	34	0.003	0.002	—	100	0	0
MS-SVDD-ω12025.02		48	83	12	49	32	0.482	0.01	—	100	0	0
MS-SVDD-ω42025.02		48	83	13	49	33	0.425	0.01	—	100	0	0
MS-SVDD-ω72025.02		48	85	12	49	32	0.849	0.007	—	100	0	0
MS-SVDD-ω82025.02		48	85	10	49	29	9.58	0.012	—	100	0	0
MS-SVDD-ω02025.02		41	71	11	44	28	0.124	0.003	—	100	0	0
MS-SVDD-ω22025.02		41	72	11	45	28	0.456	0.011	—	100	0	0
MS-SVDD-ω32025.02		41	71	11	44	28	0.249	0.007	—	100	0	0
MS-SVDD-ω52025.02		41	72	11	45	28	0.406	0.01	—	100	0	0
MS-SVDD-ω62025.02		41	71	11	44	28	1.071	0.007	—	100	0	0