Causal inference machine learning with statistical background subtraction

US11790268B1 · kind B1 · utility

Assignee

• Blue Yonder Group, Inc. · US

Inventors

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

Key dates

• Filing date: Nov 30, 2020
• Grant date: Oct 17, 2023
• Expiry date: Apr 15, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/0211
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

A system and method are disclosed to generate causal inference machine learning models employing statistical background subtraction. Embodiments include a server comprising a processor and memory. Embodiments receive historical sales data for one or more past time periods and corresponding historical data for one or more causal variables. Embodiments deconfound the cause-effect relationship of historical sales data and historical data on the one or more causal variables. Embodiments define one or more sample weights for statistical background subtraction of the historical data and perform statistical background subtraction on the historical data. Embodiments train a first machine learning model to predict an absolute individual causal effect on a considered demand quantity in relation to the one or more causal variables and one or more sample weights.