Systems and methods for concept intervals clustering for defect visibility regression

Abstract

Systems and methods for making predictions relating to products manufactured via a manufacturing process. A processor receives a plurality of input vectors associated with a plurality of output values and a plurality of time intervals. The processor clusters the plurality of input vectors based on the time intervals associated with the input vectors. The processor trains a machine learning model for each time interval of the plurality of time intervals, where the training of the machine learning model is based on the input vectors associated with the time interval, and the output values associated with the input vectors. The processor further trains a classifier for selecting one of the plurality of time intervals for input data received for a product. In one embodiment, the machine learning model associated with the time interval selected by the classifier is invoked to predict an output based on the input data.