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KDD_CUP2017

问题简要描述:

My Solution for task1 本质上是一个时间序列预测问题。预测在未来的一段时间，通过高速公路多条路径的平均时间（20min的时间窗） 给出了历史５个月的历史记录

数据预处理： 0. 数据聚合操作 ? 对数变换

  1. 缺失值处理　－　邻近插值 2.　异常值处理　－　箱线图

特征工程： 用滑动窗口的方法产生训练集 提取的特征主要有:

1.前两小时的平均时间 2.前两小时的车流量 3.节假日(one-hot　representation) 4.上周8点到10点的特征

模型选择： 1.线性回归 ? 分为数回归　quantile regression 2.LSTM 3. randomforest

模型融合： stacking

最终成绩 182/3582 top 5%

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