Patent · US Active

System and method of cyclic boosting for explainable supervised machine learning

US11544724B1 · kind B1 · utility

4Cited by

0References

14Claims

0Family size

Assignee

Blue Yonder Group, Inc. · US

Inventors

Felix Christopher Wick · Thaleischweiler-Fröschen, DE
Michael Feindt · Karlsruhe, DE

Key dates

Filing date	Oct 15, 2019
Grant date	Jan 3, 2023
Priority date	—
Expiry date	Oct 15, 2039

Classification

Technology area (CPC G)Physics
CPC primaryG06N5/045
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A system and method are disclosed including a computer and a processor and memory. The computer receives historical sales data comprising aggregated sales data for one or more items from one or more store for at least one past time period. The computer further trains a cyclic boosting model to learn model parameters by iteratively calculating for each feature and each bin factors for at least one full feature cycle. The computer further predicts one or more demand quantities during a prediction period by applying a prediction model to historical supply chain data, wherein a training period is earlier than the prediction period, and each of the one or more demand quantities is associated with at least one item of the one or more items and at least one stocking location of the one or more stocking locations during the prediction period and rendering a demand prediction feature explanation visualization.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.