MACHINE LEARNING APPARATUS, METHOD, AND STORAGE MEDIUM

Abstract

According to one embodiment, a machine learning apparatus comprising a processor. The processor acquires, by applying a first sample to a first deep learning model that processes a classification problem, a first model output containing an inference probability and/or a feature vector output. The processor determines whether an update of a label to be used as a teacher in learning of the first deep learning model is required, based on the first model output and/or the label. The processor updates the label based on the first model output and a label at a current number of updates if it is determined that the update of the label is required, and terminates the update of the label if it is determined that the update of the label is not required.

CPC Classifications