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CONTRIBUTION INCREMENTALITY MACHINE LEARNING MODELS

机译:贡献增量机器学习模型

摘要

Methods, systems, and computer programs encoded on a computer storage medium, for training and using machine learning models are disclosed. Methods include creating a model that represents relationships between user attributes, content exposures, and performance levels for a target action using organic exposure data specifying one or more organic exposures experienced by a particular user over a specified time prior to performance of a target action by the particular user and third party exposure data specifying third party exposures of a specified type of digital component to the particular user over the specified time period. Using the model, an incremental performance level attributable to each of the third party exposures at an action time when the target action was performed by the particular user is determined. Transmission criteria for at least some digital components to which the particular user was exposed are modified based on the incremental performance.
机译:公开了在计算机存储介质上编码的方法,系统和计算机程序,用于训练和使用机器学习模型。方法包括使用有机曝光数据创建表示用户属性,内容曝光和性能等级之间的关系,所述使用有机曝光数据在特定用户在表现目标操作之前在指定的时间内通过特定用户经历的一个或多个有机曝光来进行目标操作特定用户和第三方曝光数据在指定时间段内向特定用户指定指定类型的数字组件的第三方曝光。使用该模型,确定由特定用户执行目标动作的动作时间的第三方曝光的增量性能级别。基于增量性能修改特定用户的至少一些数字组件的传输标准。

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