The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 21, 2014

Filed:

Oct. 12, 2011
Applicants:

Wei-hao Lin, New York, NY (US);

Travis H. K. Green, New York, NY (US);

Robert Kaplow, New York, NY (US);

Gang Fu, Kearny, NJ (US);

Gideon S. Mann, New York, NY (US);

Inventors:

Wei-Hao Lin, New York, NY (US);

Travis H. K. Green, New York, NY (US);

Robert Kaplow, New York, NY (US);

Gang Fu, Kearny, NJ (US);

Gideon S. Mann, New York, NY (US);

Assignee:

Google Inc., Mountain View, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/18 (2006.01);
U.S. Cl.
CPC ...
Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a plurality of first training examples, training a first predictive model using the first training examples, for each example in the first training examples, providing the first features of the example to the trained first predictive model to generate a respective first prediction, generating a second training example for each of the first training examples, wherein the second training example comprises the first features of the first training example and an answer that indicates whether the first answer of the first training example matches the respective first prediction of the first training example, training a second predictive model using the second training examples, and using the trained second predictive model to determine a confidence score for a prediction generated by the trained first predictive model.


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