Device and method for training a classifier

A computer-implemented method for using a classifier for classifying sensor signals, wherein the classifier is trained to optimize performance according to a non-decomposable metric that measures an alignment between classifications corresponding to input signals of a set of training data and corresponding predicted classifications of the input signals obtained from the classifier, the training including providing weighting factors that characterize how the non-decomposable metric depends on a plurality of terms from a confusion matrix of the classifications and the predicted classifications, and training the classifier depending on the provided weighting factors, the method comprising the following steps:

• receiving a sensor signal including data from a sensor;
• determining a first input signal which depends on the sensor signal;
• and
• feeding the first input signal into the classifier to obtain an output signal that characterizes a classification of the first input signal.

A computer-implemented method for using a classifier trained for providing an actuator control signal for controlling an actuator, wherein the classifier is trained to optimize performance according to a non-decomposable metric that measures an alignment between classifications corresponding to input signals of a set of training data and corresponding predicted classifications of the input signals obtained from the classifier, the training including providing weighting factors that characterize how the non-decomposable metric depends on a plurality of terms from a confusion matrix of the classifications and the predicted classifications, and training the classifier depending on the provided weighting factors, the method comprising the following steps:

• receiving a sensor signal including data from a sensor;
• determining a first input signal which depends on the sensor signal;
• feeding the first input signal into the classifier to obtain an output signal that characterizes a classification of the first input signal;
• and
• determining the actuator control signal depending on the output signal.

A control system that is configured to use a classifier for classifying sensor signals, wherein the classifier is trained to optimize performance according to a non-decomposable metric that measures an alignment between classifications corresponding to input signals of a set of training data and corresponding predicted classifications of the input signals obtained from the classifier, the training including providing weighting factors that characterize how the non-decomposable metric depends on a plurality of terms from a confusion matrix of the classifications and the predicted classifications, and training the classifier depending on the provided weighting factors, the control system configured to:

• receive a sensor signal including data from a sensor;
• determine a first input signal which depends on the sensor signal;
• and
• feed the first input signal into the classifier to obtain an output signal that characterizes a classification of the first input signal.