DIFFICULTY-ADAPTIVE TRAINING FOR MACHINE LEARNING MODULES

摘要

A method (100) for obtaining and/or augmenting a training data set (11*) for a machine learning module (1), comprising:• providing (110) samples (11a) of training input data annotated with labels (13a) with respect to a given problem;• obtaining (120), from the samples (11a) of training input data and the associated labels (13a), a difficulty function (14) providing a measure for the difficulty (14a) of evaluating samples (11a) with respect to the given problem;• obtaining (130) at least one candidate sample (15) of training input data, and/or a representation (25) thereof in the working space (20);• calculating (140), by means of the difficulty function (14), a measure for the difficulty (14a) of evaluating this candidate sample (15), and/or the representation (25) thereof, with respect to the given problem; andin response to this difficulty meeting a predetermined criterion (150), including (160) the candidate sample (15) in the training data set (11*).