COMPUTER-IMPLEMENTED METHOD FOR GENERATING A COMBINED MACHINE LEARNING MODEL

The invention is directed to a Computer-implemented method for generating a combined machine learning model, comprising the steps: a. Providing a trained unsupervised machine learning model for anomaly detection; wherein the unsupervised machine learning model is trained on the basis of unlabeled training data (S1); b. Determining at least one output label for each data item of a plurality of data items of unlabeled application data by applying the trained unsupervised machine learning model on the unlabeled application data with the plurality of data items; wherein the at least one determined output label is an anomaly or a normal state (S2); c.Transmitting the at least one determined output label to a user for verifying the at least one determined output label via a user interface (S3); d. Receiving at least one processed output label, at least one additional data item or at least one additional output label from the user via the user interface or maintaining the at least one determined output label unprocessed depending on the verification by the user (S4); e. Training at least one additional machine learning model for anomaly detection in accordance with the at least one processed output label, the at least one additional data item or the at least one additional output label (S5); f.Generating the combined machine learning model for anomaly detection using a connection function based on the trained unsupervised machine learning model and the at least one trained additional machine learning model (S6); and g.Providing the combined machine learning model as output (S7) .Further, the invention relates to a computer program product and technical system.