US 12,141,710 B2
Methods and system for managing predictive models
Binu K. Mathew, Los Gatos, CA (US); Kit-Man Wan, Cupertino, CA (US); and Gaurav Kapoor, Sunnyvale, CA (US)
Assigned to Apple Inc., Cupertino, CA (US)
Filed by Apple Inc., Cupertino, CA (US)
Filed on Dec. 2, 2019, as Appl. No. 16/700,988.
Application 16/700,988 is a continuation of application No. 14/500,990, filed on Sep. 29, 2014, granted, now 10,528,872.
Claims priority of provisional application 62/005,791, filed on May 30, 2014.
Prior Publication US 2020/0104732 A1, Apr. 2, 2020
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 5/04 (2023.01); G06N 5/043 (2023.01); G06N 20/00 (2019.01); H04L 67/10 (2022.01)
CPC G06N 5/04 (2013.01) [G06N 5/043 (2013.01); G06N 20/00 (2019.01); H04L 67/10 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A method, comprising:
caching, by a predictive model framework provided on a mobile computing device, a predictive model into a memory of the mobile computing device, the predictive model having been generated by a server computing device using a first set of training data provided by one or more computing devices;
establishing, using the predictive model framework provided on the mobile computing device, a second set of training data that is specific to the predictive model;
receiving, by the predictive model framework, an application programming interface (“API”) call from an application executing on the mobile computing device, the API call providing the second set of training data and indicating a particular training algorithm included in the predictive model framework;
identifying, by the predictive model framework provided on the mobile computing device, a time at which to update the predictive model based on the second set of training data and the indicated training algorithm, wherein identifying the time is based at least on a power-related metric of the mobile computing device;
updating, by the predictive model framework provided on the mobile computing device, the predictive model based on the second set of training data and the indicated training algorithm to produce an updated predictive model; and
caching, by the predictive model framework provided on the mobile computing device, the updated predictive model into the memory.