Determining Whether a Given Input Record of Measurement Data Is Covered by the Training of a Trained Machine Learning Model

Abstract
A method for detecting whether a given input record of measurement data that is inputted to a trained machine learning model is in the domain and/or distribution of training examples with which the machine learning model was trained. The method includes: determining, from each training example, a training style that characterizes the domain and/or distribution to which the training example belongs; determining, from the given input record of measurement data, a test style that characterizes the domain and/or distribution to which the given record of measurement data belongs; evaluating, based on the training styles and the test style, to which extent the test style is a member of the distribution of the training styles; and based at least in part on the outcome of this evaluation, determining whether the given record of measurement data is in the domain and/or distribution of the training examples.