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TRAINING TRAINABLE MODULES WITH LEARNING DATA, THE LABELS OF WHICH ARE SUBJECT TO NOISE
TRAINING TRAINABLE MODULES WITH LEARNING DATA, THE LABELS OF WHICH ARE SUBJECT TO NOISE
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机译：使用学习数据训练可培训模块，其中的标签易受噪音影响
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摘要
The invention relates to a method (100) for training a trainable module (1), having the following steps: a plurality of modification processes (1a-1c) of the trainable module (1), said modification processes differing from one another to such a degree that the modification processes do not completely lead over to one another during a progressive learning process, are each pre-trained (110) at least using a respective sub-quantity of learning data sets (2); • learning input variable values (11a) of at least one learning data set (2) are fed (120) to all of the modification processes (1a-1c) as input variables (11); • the degree of uncertainty (13b) of output variable values (13) is ascertained from the deviation of the output variable values (13), into which each of the learning input variable values (11a) are converted by the modification processes (1a-1c), from one another and is assigned (130) to the learning data set (2) as the degree of uncertainty (2a) thereof; and • the uncertainty (2a) is used to ascertain (140) an evaluation (2b) of the learning data set (2), said evaluation being a measurement of how much the assignment of the learning output variable values (13a) relate to the learning input variable values (11a) in the learning data set (2). The invention also relates to a method (200) in which the trainable module is further operated (220) and actuates a system (50, 60, 70) using an actuation signal (5).
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