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Published at November 27

Heterogeneous Relationships of Subjects and Shapelets for Semi-supervised Multivariate Series Classification

cs.LG

cs.AI

Released Date: November 27, 2024

Authors: Mingsen Du, Meng Chen¹, Yongjian Li¹, Cun Ji², Shoushui Wei²

Aff.: ¹School of Control Science and Engineering, Shandong University, Jinan, China; ²School of Information Science and Engineering, Shandong Normal University, Jinan, China

Arxiv: http://arxiv.org/abs/2411.18043v1

	AF	FM	HMD	HB	LIB	MI	NATO	PD	SRS2	SWJ	AVG	Wins
ED	0.267	0.519	0.279	0.620	0.833	0.510	0.850	0.973	0.483	0.333	0.567	0
DTWI	0.267	0.513	0.297	0.659	0.894	0.390	0.850	0.939	0.533	0.200	0.554	0
DTWD	0.267	0.529	0.231	0.717	0.872	0.500	0.883	0.977	0.539	0.200	0.572	0
WEASEL+MUSE	0.400	0.550	0.365	0.727	0.894	0.500	0.870	0.948	0.460	0.267	0.598	0
HIVE-COTE	0.133	0.550	0.446	0.722	0.900	0.610	0.889	0.934	0.461	0.333	0.598	0
MLSTM-FCN	0.333	0.580	0.527	0.663	0.850	0.510	0.900	0.978	0.472	0.400	0.621	0
TapNet	0.200	0.470	0.338	0.751	0.878	0.590	0.939	0.980	0.550	0.133	0.583	0
MTPool	0.533	0.620	0.486	0.742	0.900	0.630	0.944	0.983	0.600	0.667	0.711	1
MF-Net	0.466	0.620	0.445	0.692	0.850	0.540	0.927	0.983	0.533	0.400	0.646	0
Smate	0.133	0.620	0.554	0.741	0.849	0.590	0.922	0.980	0.567	0.533	0.649	0
USRL	0.333	0.530	0.378	0.751	0.850	0.590	0.939	0.980	0.550	0.400	0.630	0
ShapeNet	0.400	0.580	0.338	0.338	0.856	0.610	0.883	0.977	0.578	0.533	0.609	0
DKN	0.467	0.600	0.662	0.765	0.900	0.620	0.872	0.948	0.600	0.533	0.697	1
TodyNet	0.467	0.570	0.649	0.756	0.850	0.640	0.972	0.987	0.550	0.467	0.691	1
SVP-T	0.400	0.600	0.392	0.790	0.883	0.650	0.906	0.983	0.600	0.467	0.667	0
MICOS	0.333	0.570	0.649	0.766	0.889	0.500	0.967	0.981	0.578	0.533	0.677	0
Dyformer	0.267	0.650	0.459	0.816	0.944	0.640	0.933	0.997	0.628	0.433	0.677	4
Ours	0.400	0.640	0.567	0.741	0.900	0.660	0.972	0.980	0.644	0.667	0.717	4