Machine learning device and classification device for accurately classifying into category to which content belongs

Abstract

An image acquisition unit of a machine learning device acquires n learning images assigned with labels to be used for categorization (n is a natural number larger than or equal to 2). A feature vector acquisition unit acquires a feature vector representing a feature from each of the n learning images. A vector conversion unit converts the feature vector for each of the n learning images to a similarity feature vector based on a similarity degree between the learning images. A classification condition learning unit learns a classification condition for categorizing the n learning images, based on the similarity feature vector converted by the vector conversion unit and the label assigned to each of the n learning images. A classification unit categorizes unlabeled testing images in accordance with the classification condition learned by the classification condition learning unit.