道路交通预测模型的凸组合

2010 IEEE International Conference on Data Mining Workshops Pub Date : 2010-12-13 DOI:10.1109/ICDMW.2010.23

Carlos J. Gil Bellosta

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引用次数: 2

摘要

本文描述了在IEEE ICDM 2010的数据挖掘竞赛的背景下，华沙道路交通预测问题的一种方法。描述了一种基于凸组合模型的解决方案，该模型在数据中挖掘不同的信息井。这种凸组合允许最终模型补偿来自不同底层模型的高度不相关的误差，并获得更高的预测精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Convex Combination of Models for Predicting Road Traffic

This paper describes an approach to the road traffic prediction problem in Warsaw in the context of a data mining competition that is part of the IEEE ICDM 2010. A solution based on a convex combination of models mining different wells of information within the data is described. Such convex combination allows the final model compensate highly uncorrelated errors from the different underlying models and to achieve higher prediction accuracy.

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2010 IEEE International Conference on Data Mining Workshops

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