METHOD FOR THE COMPUTER-ASSISTED CONFIGURATION OF A DATA-DRIVEN MODEL ON THE BASIS OF TRAINING DATA

摘要

The invention relates to a method for the computer-assisted configuration of a data-driven model (NN) on the basis of training data (TD). The method according to the invention is characterised in that the series of measurements (MR) are subjected to a suitable pre-processing process comprising a binning step (BS), wherein measurement characteristics (MC) which existed during the measurement of the measurement values (MW) in question are taken into consideration. A suitable data-driven model such as a neural network is then learned on the basis of the pre-processed series of measurements (MR'). This learned data-driven model (NN) makes it possible to accurately forecast target vectors in accordance with associated series of measurements (MR). The method can, for example, be used to analyse optical spectra. More particularly, it is possible to predict using the learned model whether the tissue sample for which an optical spectrum was detected represents diseased tissue.