https://sigspatial2021.sigspatial.org/sigspatial-cup/
- DIDI_keras_code_1222为keras版本的Graph2vec+类WDR模型调参后线上得分是0.122053374155646与0.122285919839553，分别存入./subs中
- DIDI_lgb_code_1379为lightGBM模型，线上得分为0.137901198225055
- pred_2021_07_24_09_40为pytorch版的类似于mlp+lstm模型，线上0.125209095406921
三者融合merage.py最终线上得分0.121501172396437，b榜0.12177，排名4/1173
Bibtex formatted citation @misc{liu2021multi, title={Multi View Spatial-Temporal Model for Travel Time Estimation}, author={ZiChuan Liu and Zhaoyang Wu and Meng Wang}, year={2021}, eprint={2109.07402}, archivePrefix={arXiv}, primaryClass={cs.LG} }