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    • 2. 发明申请
    • TRANSFORMING ATTRIBUTES FOR TRAINING AUTOMATED MODELING SYSTEMS
    • 训练自动建模系统的转换属性
    • WO2018057701A1
    • 2018-03-29
    • PCT/US2017/052659
    • 2017-09-21
    • EQUIFAX, INC.LITHERLAND, Trevis J.
    • LITHERLAND, Trevis J.HAO, LiBONDUGULA, Rajkumar
    • G06N99/00
    • In some aspects, a machine-learning model, which can transform input attribute values into a predictive or analytical output value, can be trained with training data grouped into attributes. A subset of the attributes can be selected and transformed into a transformed attribute used for training the model. The transformation can involve grouping portions of the training data for the subset of attributes into respective multi-dimensional bins. Each dimension of a multi-dimensional bin can correspond to a respective selected attribute. The transformation can also involve computing interim predictive output values. Each interim predictive output value can be generated from a respective training data portion in a respective multi-dimensional bin. The transformation can also involve computing smoothed interim output values by applying a smoothing function to the interim predictive output values. The transformation can also involve outputting the smoothed interim output values as a dataset for the transformed attribute.
    • 在一些方面,可以用分组为属性的训练数据来训练可以将输入属性值转换为预测或分析输出值的机器学习模型。 可以选择属性的子集并将其转换为用于训练模型的转换属性。 转换可以涉及将用于属性子集的训练数据的部分分组到相应的多维分箱中。 多维仓的每个维度可以对应于相应的选定属性。 转换还可以涉及计算临时预测输出值。 每个临时预测输出值可以从各个多维仓中的相应训练数据部分生成。 该变换还可以涉及通过对临时预测输出值应用平滑函数来计算平滑的临时输出值。 转换还可以包括将平滑的临时输出值作为转换属性的数据集输出。