Invention Grant
- Patent Title: Confidence threshold determination for machine-learned labeling
-
Application No.: US15214302Application Date: 2016-07-19
-
Publication No.: US10679390B1Publication Date: 2020-06-09
- Inventor: Mojtaba Solgi , Ankit Tandon , Vasudev Parameswaran
- Applicant: Uber Technologies, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Uber Technologies, Inc.
- Current Assignee: Uber Technologies, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Fenwick & West LLP
- Main IPC: G06T11/60
- IPC: G06T11/60 ; G06N7/00 ; G06K9/46 ; G06K9/62 ; G06N20/00

Abstract:
A map labeling system trains a machine-learned model using a set of training data and generates a set of test predictions for a set of test properties by applying the machine-learned model to a set of testing data. Each prediction in the set of test predictions comprises a confidence score representing the machine-learned model's confidence in the prediction. The map labeling system determines a correctness of each prediction in the set of predictions and determines a relationship between the confidence scores and the correctness of the test predictions. The map labeling system establishes a confidence threshold for the machine-learned model based on the determined relationship and labels a production property by applying the machine-learned model to production data.
Information query