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Integral criterion for model training and method of application to targeted marketing optimization

机译:模型训练的整体标准和有针对性的营销优化的应用方法

摘要

The present invention maximizes modeling results for targeted marketing within a specific working interval so that lift within the working interval is higher than that obtained using traditional modeling methods. It accomplishes this by explicitly solving for lift through sorting a target list by predicted output variable outcome, calculating the integral criterion of lift for a desired range by using known response and non-response data for the target list, iterating on a set of input parameters until overfitting occurs, and testing results against a validation set.
机译:本发明在特定的工作间隔内使针对目标市场的建模结果最大化,从而在工作间隔内的提升比使用传统建模方法获得的提升更高。它通过按预测的输出变量结果对目标列表进行排序来显式求解提升,通过使用目标列表的已知响应和非响应数据来计算所需范围的提升的积分标准,并迭代一组输入参数,从而实现提升直到发生过度拟合,然后根据验证集测试结果。

著录项

  • 公开/公告号US6640215B1

    专利类型

  • 公开/公告日2003-10-28

    原文格式PDF

  • 申请/专利权人 MARKETSWITCH CORPORATION;

    申请/专利号US20000525238

  • 发明设计人 YURI GALPERIN;VLADIMIR FISHMAN;

    申请日2000-03-15

  • 分类号G06E10/00;G06E30/00;G06F151/80;G06G70/00;

  • 国家 US

  • 入库时间 2022-08-22 00:05:19

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