Open Access
表3
本文方法与传统方法在Agnews和SST1上的性能比较
| 模型种类 | 模型 | Agnews | SST1 | |||
| 改进前F1 | 改进后F1 | 改进前F1 | 改进后F1 | |||
| RNN-based | bi-GRU | 85.82±0.23 | 89.66±0.13 | 51.96±0.01 | 52.35±0.15 | |
| RNN-Capsule | 84.54±0.24 | 88.96±0.52 | 51.31±0.06 | 51.62±0.36 | ||
| bi-LSTM | 85.54±0.18 | 89.76±0.15 | 47.64±0.26 | 51.01±0.50 | ||
| CNN-based | CNN | 83.83±0.18 | 86.68±0.07 | 51.21±0.08 | 51.55±0.27 | |
| Text-CNN | 82.69±0.12 | 87.24±0.32 | 50.01±0.49 | 50.25±0.97 | ||
| Attention-based | HAN | 84.19±0.02 | 88.35±0.12 | 51.71±0.21 | 51.85±0.97 | |
| Transformer | 84.26±0.31 | 89.25±0.02 | 50.31±0.11 | 51.25±0.12 | ||
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