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1、data存放源数据集,包括product_info.txt,product_quantity.txt,prediction_lilei_20170320.txt。各模型程序均从data里读取数据。 2、feature为最优单模型特征的生成程序,不生成预测结果,model1、model2、model3采用的都是最优单模型特征,因此均调用feature模块。 3、运行各model生成11份预测结果,相应地存放于model_result文件夹中,用于融合。 4、完成3后,运行result_merge程序读取model_result文件夹中的结果数据,并进行加权平均融合,生成最终的提交结果,并存于在submission_result中。 5、不同运行环境,生成的结果可能有差异,提交的预测结果使用的是如下的运行环境: (1)model1、model6、model7、model8、model9运行环境为python 2.7,xgboost 0.6,lightbgm 0.1 (2)model2、model3、result_merge运行环境为python 3.5.3,xgboost 0.6,lightgbm 0.1 (3)model4、model5、model10、model11运行环境为R语言3.3.2,data.table 1.10.4,xgboost 0.6-4, lubridate 1.5.6, magrittr 1.5, h2o 3.10.3.6
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