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:
Feb. 09, 2021

Filed:

Nov. 21, 2018
Applicant:

Salesforce.com, Inc., San Francisco, CA (US);

Inventors:

Kristen Noriko Muramoto, San Francisco, CA (US);

Son Thanh Chang, Oakland, CA (US);

Clement Jacques Antoine Tussoit, San Francisco, CA (US);

Melissa Hoang, San Francisco, CA (US);

Chaitanya Malla, Fremont, CA (US);

Orjan N. Kjellberg, Walnut Creek, CA (US);

Carlos Enrique Mogollan Jimenez, San Francisco, CA (US);

George Hu, San Francisco, CA (US);

Assignee:

salesforce.com, inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/04 (2006.01); G06F 9/451 (2018.01); G06N 99/00 (2019.01); G06F 3/0484 (2013.01); G06F 3/0482 (2013.01);
U.S. Cl.
CPC ...
G06N 5/048 (2013.01); G06F 3/0482 (2013.01); G06F 3/04847 (2013.01); G06F 9/451 (2018.02); G06N 99/00 (2013.01);
Abstract

A method of training a predictive model to predict a likely field value for one or more user selected fields within an application. The method comprises providing a user interface for user selection of the one or more user selected fields within the application; analyzing a pre-existing, user provided data set of objects; training, based on the analysis, the predictive model; determining, for each user selected field based on the analysis, a confidence function for the predictive model that identifies the percentage of cases predicted correctly at different applied confidence levels, the percentage of cases predicted incorrectly at different applied confidence levels, and the percentage of cases in which the prediction model could not provide a prediction at different applied confidence levels; and providing a user interface for user review of the confidence functions for user selection of confidence threshold levels to be used with the predictive model.


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