METHODS, SYSTEMS, AND MEDIA FOR IDENTIFYING ERRORS IN PREDICTIVE MODELS USING ANNOTATORS
Patent №
US 10,846,600
Granted
2020-11-24
Filed 2016
Owner
NEW YORK UNIVERSITY
+1 more
Lab
—
AI components
6
ml · nlp · vision · kr · planning · hardware
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
15094419
Methods, systems, and media for identifying errors in predictive models using annotators are provided. In some embodiments, a method for evaluating predictive models in classification systems is provided, the method comprising: causing an input region to be presented to a user, where the input region receives an instance from the user that corresponds to a predictive model; retrieving a classification conducted by the predictive model for the received instance and a confidence value associated with the classification; determining whether the received instance has been incorrectly classified by the predictive model; determining a reward associated with the incorrect classification made by the predictive model in response to determining that the received instance has been incorrectly classified by the predictive model, where the reward is based on the confidence value associated with the classification of the received instance; and providing the reward to the user.
AI classification
Ownership
NEW YORK UNIVERSITY
assignment · 459020753
INTEGRAL AD SCIENCE, INC.
assignment · 459020766
Assignors
IPEIROTIS, PANAGIOTIS G., PROVOST, FOSTER J.
On an employer assignment, the assignors are typically the inventors.