METHOD FOR MACHINE LEARNING BASED ON SEMI-SUPERVISED LEARNING AND APPARATUS THEREOF

摘要

Provided are a method for machine learning based on semi-supervised learning and an apparatus thereof. According to some embodiments of the present disclosure, the method may accurately select data to be additionally learned in a data set to which label information is not given based on the final output probability distribution of a first model, a second model in which learning is performed with data less than data of the first model, and a third model learning the final output probability distribution of the first model. In addition, by additionally learning prediction label information of the selected data, the performance of a machine learning model may be gradually improved.