US 12,437,344 B2
Method of controlling for undesired factors in machine learning models
Jeffrey S. Myers, Normal, IL (US); Kenneth J. Sanchez, San Francisco, CA (US); and Michael L. Bernico, Bloomington, IL (US)
Assigned to State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed by State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed on Apr. 29, 2024, as Appl. No. 18/649,545.
Application 18/649,545 is a continuation of application No. 17/963,397, filed on Oct. 11, 2022, granted, now 12,014,426.
Application 17/963,397 is a continuation of application No. 16/893,041, filed on Jun. 4, 2020, granted, now 11,501,133, issued on Nov. 15, 2022.
Application 16/893,041 is a continuation of application No. 15/383,499, filed on Dec. 19, 2016, granted, now 10,769,518, issued on Sep. 8, 2020.
Claims priority of provisional application 62/273,624, filed on Dec. 31, 2015.
Claims priority of provisional application 62/272,184, filed on Dec. 29, 2015.
Prior Publication US 2024/0281894 A1, Aug. 22, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06Q 40/08 (2012.01); G06V 10/82 (2022.01); G06V 30/19 (2022.01); G06V 40/16 (2022.01); H04N 7/18 (2006.01); G06Q 30/0207 (2023.01)
CPC G06Q 40/08 (2013.01) [G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06V 10/82 (2022.01); G06V 30/19173 (2022.01); G06V 40/169 (2022.01); H04N 7/185 (2013.01); G06Q 30/0207 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer system configured to train a machine learning model, the computer system comprising one or more processors configured to:
receive an unstructured training data set including at least one of images or audio of a plurality of individuals;
train the machine learning model using the unstructured training data set to produce a first trained machine learning model that includes one or more undesired factors;
identify the one or more undesired factors included in the first trained machine learning model;
train the first trained machine learning model based upon the identified one or more undesired factors to produce a second trained machine learning model trained to identify the identified one or more undesired factors; and
run the second trained machine learning model to analyze at least one of images or audio of an individual while excluding some or all of the identified one or more undesired factors.