公开(公告)号：US20240362538A1

公开(公告)日：2024-10-31

申请号：US18645222

申请日：2024-04-24

申请人： Daash Intelligence, Inc.

发明人： Justin T. Stewart ,  Philip M. Smolin ,  Melissa S. Munnerlyn ,  Liam N. Isaacs ,  Phillip J. Markert ,  Vinoad Senguttuvan

IPC分类号： G06N20/00

CPC分类号： G06N20/00

摘要： A method of training a machine learning regression model includes defining a prediction accuracy grading function, the prediction accuracy grading function being a many-to-one function that maps prediction accuracies to proxies, each of the prediction accuracies being derivable from a respective prediction of the model and a corresponding actual. The method may further include receiving a plurality of proxies corresponding respectively to a plurality of predictions of the model and, for each of the plurality of proxies, deriving a corresponding approximated actual according to the prediction accuracy grading function. The method may further include calculating an approximated residual for each of the plurality of predictions of the model based on the corresponding approximated actual and adjusting the model based on the approximated residuals.