In order to enable machine learning to be carried out more efficiently, a dictionary learning device 1 is equipped with an importance calculation unit 2 and a data selection unit 3. On the basis of feature vectors, multiple items of teaching data are arranged in a feature space having, as variables, elements that constitute a feature vector in the teaching data. In this case, for each unlabeled data item included in the multiple items of teaching data the importance calculation unit 2 calculates the importance of the unlabeled data item, on the basis of the density of labeled data in the teaching data in a region having a size that has been set by using that unlabeled data as a standard. On the basis of information representing the closeness of an unlabeled data item and a discrimination boundary based on a discrimination function serving as a basis for discriminating data, and information representing the importance from the importance calculation unit 2, the data selectin unit 3 selects data to be labeled from among the multiple items of unlabeled data.
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