kee's Introduction
# raw data 链接: https://pan.baidu.com/s/1kUTZW6V 密码: ug9x # 数据生成过程及解释 原始数据: t_click.csv, t_loan.csv, t_loan_sum.csv, t_order.csv, t_user.csv DataDescription中定义了5个表对应的具体类: Click,Loan,LoanSum,Order,User。 配套有convertXXX和loadXXX方法,convertXXX用来将csv文件转成以上面类定义的parquet文件,loadXXX方法用来加载parquet数据。 Click,Loan,LoanSum,Order,User这5个数据,通过DataDescription.joinData()方法拼成一个完整的User数据。 即,将Loan,Order,Click这些数据聚合成数组,再按uid和User join上得到的。比如,User.clicks包含,该user的所有Click。 从User数据生成RawFeature: RawFeature用来表示进一步数据处理之后的大宽表。比如将Click按月切分统计等等操作。主要在DataDescription.generateData()方法中。 从RawFeature生成样本数据: 通过比照FeatureUtils.feByMonth可以新增生成样本的逻辑。主要用来,选择哪些列,具体的列作为离散or连续特征,label取哪个字段。
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