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SYSTEM AND METHOD FOR EXTRACTION AND CONVERSION OF ELECTRONIC HEALTH INFORMATION FOR TRAINING A COMPUTERIZED DATA MODEL FOR ALGORITHMIC DETECTION OF NON-LINEARITY IN A DATA SET
SYSTEM AND METHOD FOR EXTRACTION AND CONVERSION OF ELECTRONIC HEALTH INFORMATION FOR TRAINING A COMPUTERIZED DATA MODEL FOR ALGORITHMIC DETECTION OF NON-LINEARITY IN A DATA SET
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机译:电子健康信息的提取和转换以训练用于计算数据集中非线性度的计算机数据模型的系统和方法
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摘要
A system and method for training a computerized data model for the algorithmic detection of non-linearity in a data set includes providing two master data sets corresponding to two discrete time periods, respectively, and a third data set for a third discrete time period. The two master data sets are mapped to at least one code model. A stacking average model is trained with the at least two master data sets corresponding to two discrete time periods by using a stacked regression algorithm. A box-cox transformation function is applied to the models to provide a predicted value for the third data set of the third discrete time period. An ensemble is created using the predicted value for the third data set and the first, second, and third models of the trained stacking average model to identify a non-linearity in the third data set.
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