Supervised machine learning of a computer-implemented method for performing a technical process, computer program and a computer-readable storage medium having a computer program for implementing the method

A supervised machine learning of a computer-implemented method for performing a technical process in which output variables of the technical process resulting from input variables can be ascertained, the method comprises the following steps of:

• a) creating a data pool, containing data sets with input data for the technical process and output data that is assigned to the input data and describes a correct process result;
• b) dividing the data sets in the data pool into training data sets and validation data sets;
• c) training the computer-implemented method using the training data sets in a training phase, wherein process parameters of the computer-implemented method are varied during repeated performances of the computer-implemented method;
• d) checking a trained computer-implemented method using the validation data sets in a validation phase by comparing the output data calculated with the trained computer-implemented method with the input data, with the output data describing the correct process result and calculating an actual probability of failure for the computer-implemented method as a result of a comparison;
• e) defining a safety factor related to a target probability of failure for the training phase, with which an empirical probability of failure is calculated, which is lower than the target probability of failure, wherein the empirical probability of failure is reduced by a confidence level compared to the target probability of failure;
• and
• f) initiating the validation phase after it has been established in the training phase that the empirical probability of failure is not exceeded.