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    Predictive model augmentation by variable transformation
    28.
    发明授权
    Predictive model augmentation by variable transformation 失效
    通过变量变换预测模型增加

    公开(公告)号：US07730003B2

    公开(公告)日：2010-06-01

    申请号：US10826950

    申请日：2004-04-16

    Applicant: Stephen K. Pinto ,  Richard Mansfield ,  Marc Jacobs ,  Donald Rubin

    Inventor： Stephen K. Pinto ,  Richard Mansfield ,  Marc Jacobs ,  Donald Rubin

    IPC: G06E1/00 ,  G06E3/00

    CPC classification number: G06Q10/04 ,  G06Q30/0201

    Abstract: Models are generated using a variety of tools and features of a model generation platform. For example, in connection with a project in which a user generates a predictive model based on historical data about a system being modeled, the user is provided through a graphical user interface a structured sequence of model generation activities to be followed, the sequence including dimension reduction, model generation, model process validation, and model re-generation.Historical multi-dimensional data is received representing multiple source variables to be used as an input to a predictive model of a commercial system and applying transformations to the data that are selected based on the strength of measurement represented by a variable; variables are transformed into new more predictive variables, including the Bayesian renormalization of sparsely sampled variable and including the imputation of missing values for categorical or continuous variables.

    Abstract translation: 使用模型生成平台的各种工具和功能生成模型。 例如，关于用户根据关于正被建模的系统的历史数据生成预测模型的项目，通过图形用户界面提供要遵循的模型生成活动的结构化序列，所述序列包括维度 减少，模型生成，模型过程验证和模型重新生成。 接收表示多个源变量的历史多维数据，以用作商业系统的预测模型的输入，并且基于由变量表示的测量强度来选择的数据进行变换; 变量被变换成新的更具预测性的变量，包括稀疏抽样变量的贝叶斯重正化，包括对分类或连续变量的缺失值的插补。

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