CORRECTING MACHINE-LEARNING MODEL TRAINING DATA

Proposed concepts thus aim to provide schemes, solutions, concepts, designs, methods and systems pertaining to improving (i.e. increasing accuracy and/or reliability) machine-learning models by correcting data used to train such models. In particular, a timestamp of training data describing an event is modified according to a time-shift function and a predetermined time uncertainty range. In this way, an uncertainty/inaccuracy of the recording of the timestamp may be compensated for, such that a quality of the training data may be improved.