ETA预测的层次定位方法

Proceedings of the 29th International Conference on Advances in Geographic Information Systems Pub Date : 2021-11-02 DOI:10.1145/3474717.3488240

Tomoki Saito, Shinichi Tanimoto, Fumihiko Takahashi

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引用次数: 0

摘要

GISCUP 2021的重点是预计到达时间(ETA)，广泛应用于交通运输和移动等各个行业。在本文中，我们描述了从宽到窄分层使用位置特征和其他统计特征进行GBDT预测的第6位解决方案。特别是对于窄特征，通过扩展node2vec生成图嵌入特征，使其更容易处理大量数据。该方案的MAPE得分为12.478。

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Hierarchical Positional Approach for ETA Prediction

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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Proceedings of the 29th International Conference on Advances in Geographic Information Systems

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