公开(公告)号：US20240428054A1

公开(公告)日：2024-12-26

申请号：US18684043

申请日：2022-08-17

Applicant: BASF SE

Inventor： Iain Proctor ,  Eduard Szoecs ,  Georgios Kritikos ,  Till Eggers

IPC: G06N3/0464

Abstract: The present invention relates to validating a linear model. Input data is received (102) and the linear model to be validated is provided (104). Predicted data is determined based on processing input data by the linear model (106). Residual data is determined based on a difference between the predicted data and the input data (108). A set of validation data including homoscedasticity validation data or normality validation data is generated based on the residual data (110). A binary classifier is provided and used for determining whether the set of validation data fulfills a validation condition (112), namely a homoscedasticity condition or a normality condition. The binary classifier is a trained data driven model that outputs that the validation condition is fulfilled or not fulfilled depending on the set of validation data. Finally, it is determined whether the linear model is valid based on the output of the binary classifier (114).