US 12,243,106 B2
Technology for building and managing data models
Weixin Wu, Bloomington, IL (US); Philip Sangpil Moon, Bloomington, IL (US); and Scott Farris, 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 Jul. 12, 2023, as Appl. No. 18/221,023.
Application 18/221,023 is a continuation of application No. 15/977,677, filed on May 11, 2018, granted, now 11,775,619.
Claims priority of provisional application 62/633,859, filed on Feb. 22, 2018.
Claims priority of provisional application 62/632,679, filed on Feb. 20, 2018.
Claims priority of provisional application 62/621,784, filed on Jan. 25, 2018.
Claims priority of provisional application 62/615,286, filed on Jan. 9, 2018.
Claims priority of provisional application 62/592,975, filed on Nov. 30, 2017.
Claims priority of provisional application 62/589,444, filed on Nov. 21, 2017.
Prior Publication US 2024/0012882 A1, Jan. 11, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 40/08 (2012.01); G06F 8/35 (2018.01); G06F 16/904 (2019.01); G06F 17/18 (2006.01); G06F 18/21 (2023.01); G06F 18/40 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01)
CPC G06Q 40/08 (2013.01) [G06F 8/35 (2013.01); G06F 16/904 (2019.01); G06F 17/18 (2013.01); G06F 18/2163 (2023.01); G06F 18/2193 (2023.01); G06F 18/40 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method in a computing device of enabling the management of data models, the method comprising:
generating, by a computer processor, a model build partition, including enabling a user to input, via a user interface:
a storage location where a modeling output is to be stored,
a set of variables to be binned,
a set of identifications for (i) at least one of a training dataset and a validation dataset, and (ii) modeling data, and
a set of selections associated with (i) whether to generate the modeling output using the training dataset and the validation dataset, or using the training dataset, (ii) a model iteration identification, and (iii) a set of model effects;
generating, by the processor, the modeling output according to the model build partition; and
displaying, in the user interface, a set of results associated with generating the modeling output, the set of results including: (a) a set of model level results, and (b) a set of variable level results.