US 12,229,639 B2
Acceptance status classification of product-related data structures using models with multiple training periods
Noga Gershon, Dimona (IL); and Amihai Savir, Sansana (IL)
Assigned to EMC IP Holding Company LLC, Hopkinton, MA (US)
Filed by EMC IP Holding Company LLC, Hopkinton, MA (US)
Filed on Oct. 23, 2020, as Appl. No. 17/078,675.
Prior Publication US 2022/0129783 A1, Apr. 28, 2022
Int. Cl. G06N 20/00 (2019.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01)
CPC G06N 20/00 (2019.01) [G06F 18/213 (2023.01); G06F 18/2148 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
obtaining data for a given product-related data structure;
evaluating a plurality of first features related to the given product-related data structure using the obtained data;
applying the plurality of first features related to the given product-related data structure to a plurality of models to obtain a corresponding plurality of second features, wherein each of the plurality of second features indicates a prediction related to an acceptance status of the given product-related data structure by a respective one of the models for a respective training period, wherein the plurality of models is trained using training data from a respective one of a plurality of different training periods, wherein each different training period comprises a different time duration of the training data, and wherein the plurality of first features is distinct from the respective time duration of the training data for the plurality of models, wherein the plurality of second features comprises respective ones of a plurality of acceptance status predictions, associated with respective ones of the plurality of different training periods, wherein the plurality of acceptance status predictions and one or more of the plurality of first features are applied to a classification engine that generates an aggregate acceptance status; and
aggregating at least the plurality of second features to obtain a classification related to the aggregate acceptance status of the given product-related data structure;
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.