Abstract
The GISCUP 2021 focuses on estimated time of arrival (ETA) which is widely used in various industries such as Transportation and Mobility. In this paper, we describe the 6th-place-solution that uses positional features hierarchically from wide to narrow and other statistical features for predictions with GBDT. Especially for narrow features, graph-embedding features are generated by extending node2vec to make it easier to handle large amounts of data. This solution got MAPE score of 12.478 as the final score.
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CITATION STYLE
Saito, T., Tanimoto, S., & Takahashi, F. (2021). Hierarchical Positional Approach for ETA Prediction. In GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems (pp. 650–653). Association for Computing Machinery. https://doi.org/10.1145/3474717.3488240
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