1. A machine learning device comprising: a content acquirer that acquires n learning contents (n is a natural number larger than or equal to 2) with a label to be used for categorization; a feature vector acquirer that acquires a feature vector from each of the n learning contents acquired by the content acquirer; a vector converter that converts the feature vectors for the n learning contents acquired by the feature vector acquirer to similarity feature vectors based on similarity degrees between the learning contents; a condition learning device that learns a classification condition for categorizing the n learning contents based on the similarity feature vectors converted by the vector converter and a label assigned to each of the n learning contents; and a classifier that categorizes a testing content to which the label is not assigned, in accordance with the classification condition learned by the condition learning device.