公开(公告)号：US20250068983A1

公开(公告)日：2025-02-27

申请号：US18237234

申请日：2023-08-23

Applicant: Oracle International Corporation

Inventor： Olaitan Olaleye ,  Hitesh Laxmichand Patel ,  Tao Sheng

IPC: G06N20/20

Abstract: In some implementations, the techniques may include receiving an accuracy target for one or more machine learning models. In addition, the techniques may include training the models on a labeled training set of labeled data. The techniques may include, until the accuracy of the models satisfies the accuracy target: sampling, a set of unlabeled data to obtain a random training set of unlabeled data; labeling the random training set of unlabeled data using the models to produce a pseudo labeled training set; correcting the labels on a random subset of the pseudo labeled training set; training the models on the labeled training set, the corrected random subset, and the pseudo labeled training set; and evaluating the accuracy of the models using an evaluation set of labeled data. The one or more models can be deployed based at least in part on the models satisfying the accuracy target.