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

Planning1.00
Machine learning1.00
Natural language1.00
Knowledge representation1.00
Vision1.00
AI hardware1.00
Evolutionary computation0.25
Speech0.01

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.

From the same owner

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