TRAINING OF MACHINE LEARNING MODELS FOR DATA-DRIVEN DECISION-MAKING

摘要

The invention relates to a method for training machine learning models (51), having the steps of: detecting (S10) data (70) in the form of time series data using one or more computers (52), said data being obtained by means of one or more measuring devices (60-62), in each case in the form of a sensor for measuring a physical variable; receiving (S12) multiple classification data units relating to the data (70) using the one or more computers (52); receiving (S13) a selected part (71) of the data (70) using the one or more computers (52) for each of the classification data units; and training (S14) multiple machine learning models (51) using the one or more computers (52), in each case on the basis of at least one of the classification data units and the at least one corresponding selected part (71) of the data, wherein the multiple machine learning models (51) represent multiple instances of the same machine learning model.