Abstract: The invention provides a control arrangement where the controller is arranged to drive the actuator utilizing automatically the explanation values. The control arrangement has a controller, which is arranged to drive an actuator. The control arrangement comprises also a setpoint controller, which is arranged to utilize deviations between explanation values of machine learning and normal explanation values of machine learning. The setpoint controller forms a setpoint value for the controller.

Abstract: The invention provides a diagnostic arrangement, which utilizes pre-processed measurement data, ML values and explanation values. By using all these values/data it is possible to analyse phenomenon, events, and behaviour of the process in such a way that a number of aspects can be taken into account.

Abstract: The invention provides a way to monitor a process (1). The invention utilizes explanation values. A ML model of the process is created. The ML model utilizes measurements from the process as inputs to the ML model and forms model outputs. The inputs are classified to groups in the. The explanation values are calculated for each input indicating contribution of the input to the model output/s, and a sum of the explanation values for each group are calculated. The calculated sums are monitored, each sum indicating status of the group in question.