HAR
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Time Series Classification | HAR | Accuracy98.83 | 39 | |
| Classification | HAR 5% labels | Accuracy93.14 | 19 | |
| Classification | HAR (1% labels) | Accuracy84.16 | 19 | |
| Multivariate Time Series Classification | HAR | Accuracy96.71 | 15 | |
| Classification | HAR (test) | Accuracy93.35 | 15 | |
| Human Activity Recognition | HAR Average Across 8 Datasets | Accuracy81.6 | 14 | |
| Classification | HAR | Accuracy92.98 | 13 | |
| Human Activity Recognition | HAR dataset (ALL) | Accuracy95.77 | 12 | |
| Human Activity Recognition | HAR dataset patient08 | Accuracy97.09 | 12 | |
| Human Activity Recognition | HAR dataset patient06 | Accuracy97.48 | 12 | |
| Human Activity Recognition | HAR dataset patient05 | Accuracy97.7 | 12 | |
| Human Activity Recognition | HAR dataset patient04 | Accuracy93.77 | 12 | |
| Human Activity Recognition | HAR patient03 | Accuracy97.31 | 12 | |
| Human Activity Recognition | HAR dataset patient02 | Accuracy95.25 | 12 | |
| Human Activity Recognition | HAR | Time per Sweep (s)7.53 | 12 | |
| Human Activity Recognition | HAR Real-world Setting (test) | Accuracy79.72 | 11 | |
| Human Activity Recognition | HAR 30 FL clients, 1000 global iterations & Logistic Regression model (Cross-silo) | A Theta Performance97.21 | 10 | |
| Neural Architecture Search | HAR search space | Accuracy0.9612 | 10 | |
| Closed-set activity classification | HAR (XP) | Accuracy68.3 | 9 | |
| Closed-set activity classification | HAR (XS) | Accuracy85.1 | 9 | |
| Clustering | HAR (train) | Runtime (s)0.13 | 9 | |
| Activity Recognition | HAR70+ | Accuracy68.2 | 9 | |
| Classification | HAR | Accuracy0.917 | 8 | |
| Imputation | HAR | MSE0.29 | 8 | |
| Time Series Imputation | HAR MNAR (test) | MSE0.29 | 8 |
Showing 25 of 47 rows