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公开(公告)号：US10417528B2
公开(公告)日：2019-09-17
申请号：US16059241
申请日：2018-08-09
Applicant: SAS Institute Inc.
Inventor： Yongjin Ma , Xinmin Wu , Xiaomei Liu
Abstract: An assessment dataset is selected from an input dataset using a first stratified sampling process based on a value of an event assessment variable. A remainder of the input dataset is allocated to a training/validation dataset that is partitioned into an oversampled training/validation dataset using an oversampling process based on a predefined value of the event assessment variable. A validation sample is selected from the oversampled training/validation dataset using a second stratified sampling process based on the value of the event assessment variable. A training sample is selected from the oversampled training/validation dataset using the second stratified sampling process based on the value of the event assessment variable. The validation sample and the training sample are mutually exclusive. A predictive type model is trained using the selected training sample. A plurality of predictive type models are trained, validated, and scored using the samples to select a best predictive model.
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公开(公告)号：US20190258904A1
公开(公告)日：2019-08-22
申请号：US16059241
申请日：2018-08-09
Applicant: SAS Institute Inc.
Inventor： Yongjin Ma , Xinmin Wu , Xiaomei Liu
Abstract: An assessment dataset is selected from an input dataset using a first stratified sampling process based on a value of an event assessment variable. A remainder of the input dataset is allocated to a training/validation dataset that is partitioned into an oversampled training/validation dataset using an oversampling process based on a predefined value of the event assessment variable. A validation sample is selected from the oversampled training/validation dataset using a second stratified sampling process based on the value of the event assessment variable. A training sample is selected from the oversampled training/validation dataset using the second stratified sampling process based on the value of the event assessment variable. The validation sample and the training sample are mutually exclusive. A predictive type model is trained using the selected training sample. A plurality of predictive type models are trained, validated, and scored using the samples to select a best predictive model.
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