METHOD AND SYSTEM FOR TRAINING A MACHINE LEARNING ALGORITHM FOR SELECTING PROCESS PARAMETERS FOR AN INDUSTRIAL PROCESS

摘要

A method of training a Machine Learning Algorithm for selecting process parameters for an industrial process, the method comprising: generating a training set for training the MLA, the training set comprising a plurality of feature vectors and respectively associated estimation errors, the generating comprises: generating the plurality of feature vectors based on history data associated with an industrial process; identifying a respective value of a target process feature within each feature vector; computing a regression function; determining an estimated outcome value for each respective value of the target process feature based on the regression function; and computing the estimation error for each feature vector based on the respectively associated outcome value and the respectively associated estimated outcome value. The method also comprises training the MLA based on the training set for predicting the respective estimation error for each feature vector, the training the MLA comprises inputting each feature vector and the respectively associated estimation error into the MLA.