公开(公告)号：EP3832550A1

公开(公告)日：2021-06-09

申请号：EP19212867.6

申请日：2019-12-02

申请人： Robert Bosch GmbH ,  Carnegie Mellon University

发明人： Kolter, Jeremy Zieg ,  Schmidt, Frank ,  Fathony, Rizal

IPC分类号： G06N3/04 ,  G06N3/08

摘要： A computer-implemented method for training a classifier (60), particularly a binary classifier, for classifying input signals ( x i ) to optimize performance according to a non-decomposable metric that measures an alignment between classifications ( y i ) corresponding to input signals ( x i ) of a set of training data and corresponding predicted classifications ( ŷ i ) of said input signals obtained from said classifier, comprising the steps of:
- providing weighting factors that characterize how said non-decomposable metric depends on a plurality of terms from a confusion matrix of said classifications ( y i ) and said predicted classifications ( ŷ i );
- training said classifier (60) depending on said provided weighting factors.