Patent ID: 11914606
Assignee: WALMART APOLLO, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 10:
11. A method being implemented via execution of computing instructions configured to run at one or more processors and stored at non-transitory computer-readable media, the method comprising:
receiving, from an extraction, transform, load (ETL) application, a matrix comprising raw feature data;
storing the matrix comprising the raw feature data in a standard format in one or more storage devices;
receiving a configuration file over a computer network, wherein the configuration file is configured to identify features for use in a respective machine learning algorithm and a time period in which to collect the features, and wherein the configuration file is further configured to be transferable between machine learning models using a same set of unifiers and feature data;
storing the configuration file in a standard format in the one or more storage devices;
reading one or more tuples in the configuration file, as stored;
instantiating one or more unifier applications specified in a first portion of a respective tuple in the one or more tuples in the configuration file;
identifying selected feature data of the raw feature data using the configuration file and the one or more unifier applications;
collecting, by the one or more unifier applications, historical transactions at a division level for users over the time period;
creating, by the one or more unifier applications, subsets of the historical transactions within the time period;
storing the selected feature data in a training schema format and the subset of the historical transactions in an output file in the one or more storage devices, wherein the training schema format comprises at least one synthetic feature generated as a function of two or more pre-existing features;
transmitting, over the computer network in real time to a model building system, the output file comprising the selected feature data from the one or more storage devices for use in a machine learning application;
training a machine learning model of the machine learning application on the selected feature data in the training schema format using the model building system and one or more building applications; and
generating a machine learning algorithm for the machine learning model based on parameters in the output file, wherein the output file is configured to be transferred between different machine learning models.