Time-series Classification on UCI-HAR (Accuracy and Resource Usage) benchmark leaderboard · SOTA2 Research

Time-series Classification on UCI-HAR (Accuracy and Resource Usage)

90.8AccuracyMONAQ

Evaluation Results

Method	Links
MONAQ2025.05		90.8	14.176	10.508	53,936	0.0003	18.675
TENet2025.05		90.4	171.28	142.228	3,796,960	0.0055	494.159
TinyTNAS2025.05		85.8	25.128	11.816	160,134	0.0002	22.373
DS-CNN2025.05		82.2	14.288	16.904	183,110	0.0003	30.229
CNN2025.05		81.9	12.872	13.016	707,792	0.0003	49.271
GPT-4o2025.05		81.7	110.848	9.052	285,760	0.0002	26.284
GPT-4o-mini2025.05		81.4	223.432	16.092	901,440	0.0005	57.644
TCN2025.05		81.3	34.704	13.696	454,896	0.0011	81.811
Random Search2025.05		80.5	18.104	12.188	9,583	0.0003	11.021
Grid Search2025.05		78.3	18.8	11.08	23,700	0.0002	11.759
MLP2025.05		78.1	23.968	2.46	20,464	0	1.151
D-CNN2025.05		62.7	7.256	3.8	9,261	0	4.513
LSTM2025.05		34.8	9.128	8.208	48	0	0.086
ConvLSTM2025.05		34.8	10.992	15.924	58,928	0.0001	16.282