公开(公告)号：US20240265304A1

公开(公告)日：2024-08-08

申请号：US18336538

申请日：2023-06-16

申请人： Optum, Inc.

发明人： Dominik Roman Christian DAHLEM ,  Eran HALPERIN ,  James ZOU ,  Kevin WU

IPC分类号： G06N20/00

CPC分类号： G06N20/00

摘要： Various embodiments of the present disclosure provide techniques for optimally augmenting a training dataset for a machine learning model based on multiple model-focused predictions. The techniques may include generating a datapoint priority matrix that corresponds to a plurality of entity-feature value pairs of a training dataset for a machine learning model, generating a plurality of impact predictions and feature sensitivity predictions for the plurality of entity-feature value pairs, generating a refined datapoint priority matrix by updating the datapoint priority matrix based on the plurality of impact predictions and sensitivity predictions, and providing a datapoint collection output for the training dataset based on the refined datapoint priority matrix and a data augmentation threshold.