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    • 2. 发明授权
    • Incremental effect modeling by area index maximization
    • 面积指数最大化的增量效应建模
    • US08818920B2
    • 2014-08-26
    • US13416149
    • 2012-03-09
    • Xiaohu LiuJing Li
    • Xiaohu LiuJing Li
    • G06F15/18
    • G06N99/005G06Q10/06G06Q30/00
    • How much is the net benefit of treating an individual: cost-effective, very small, or even negative? To address this question, a methodology for developing an incremental effect model based on randomized test data is provided. The concept of an incremental effect area index is introduced for measuring the model's quality. A new variable screening technique is proposed to identify variables that are decision relevant and preferably time invariant. A piecewise linear function is created for each continuous variable to approximate the relationship between the incremental effect and the variable, based on a binning technique. Finally, a score is created as the weighted sum of a set of functions, with each function being the empirical prediction of the incremental effect based on a variable, wherein weights are chosen to maximize the incremental effect area index. The methodology creates an improved incremental effect model, leading to more cost-effective strategies in business practice.
    • 治疗个体的净收益多少?成本有效,非常小甚至是负面的? 为了解决这个问题,提供了一种基于随机测试数据开发增量效应模型的方法。 引入增量效应面积指数的概念来衡量模型的质量。 提出了一种新的变量筛选技术来确定与决策有关的变量,优选时变不变。 基于分档技术,为每个连续变量创建分段线性函数以近似增量效应和变量之间的关系。 最后,创建一个分数作为一组函数的加权和,每个函数是基于变量的增量效应的经验预测,其中选择权重以使增量效应面积指数最大化。 该方法创建了一个改进的增量效应模型,从而在业务实践中实现更具成本效益的策略。
    • 4. 发明申请
    • INCREMENTAL EFFECT MODELING BY AREA INDEX MAXIMIZATION
    • 区域索引最大化的增量效应建模
    • US20130238539A1
    • 2013-09-12
    • US13416149
    • 2012-03-09
    • Xiaohu LiuJing Li
    • Xiaohu LiuJing Li
    • G06N5/02G06F17/00
    • G06N99/005G06Q10/06G06Q30/00
    • How much is the net benefit of treating an individual: cost-effective, very small, or even negative? To address this question, a methodology for developing an incremental effect model based on randomized test data is provided. The concept of an incremental effect area index is introduced for measuring the model's quality. A new variable screening technique is proposed to identify variables that are decision relevant and preferably time invariant. A piecewise linear function is created for each continuous variable to approximate the relationship between the incremental effect and the variable, based on a binning technique. Finally, a score is created as the weighted sum of a set of functions, with each function being the empirical prediction of the incremental effect based on a variable, wherein weights are chosen to maximize the incremental effect area index. The methodology creates an improved incremental effect model, leading to more cost-effective strategies in business practice.
    • 治疗个体的净收益多少?成本有效,非常小甚至是负面的? 为了解决这个问题,提供了一种基于随机测试数据开发增量效应模型的方法。 引入增量效应面积指数的概念来衡量模型的质量。 提出了一种新的变量筛选技术来确定与决策有关的变量,优选时变不变。 基于分档技术,为每个连续变量创建分段线性函数以近似增量效应和变量之间的关系。 最后,创建一个分数作为一组函数的加权和,每个函数是基于变量的增量效应的经验预测,其中选择权重以使增量效应面积指数最大化。 该方法创建了一个改进的增量效应模型,从而在业务实践中实现更具成本效益的策略。