1. A recognition device comprising: a generation unit configured to perform, plural times, a selection process of selecting a plurality of groups each including one or more learning samples from a learning sample storage unit that stores therein a plurality of learning samples that are classified into a plurality of categories, learn a classification metric, which is a classifier F i (x) for each group of the plurality of groups for classifying the plurality of groups selected in each selection process, where 1≦i≦N, and N is the number of classifiers, and perform a generation process of generating an evaluation metric that includes the classifier F i (x) for each group of the plurality of groups, wherein the evaluation metric is defined as {F 1 (x), F 2 (x), through, F N (x)}, and wherein x is a variable; a first reception unit configured to receive an image including an object as a recognition target; an extraction unit configured to extract a first feature value representing an image feature of the image; a transformation unit configured to transform the first feature value into a second feature value using the evaluation metric; a calculation unit configured to calculate, by referring to a recognition table stored in a recognition table storage unit in which a plurality of reference feature values, stored as recognition metrics, and categories are associated with each other, similarity of the object to each category included in the recognition table using the second feature value and the plurality of reference features; an output control unit configured to output the similarity of the object to each category included in the recognition table to an output unit as a result of recognition; a second reception unit configured to receive a category of the object; and a registration unit configured to register the second feature value as the reference feature value in the recognition table with being associated with the category of the object and register the first feature value as the learning sample belonging to the category of the object in the learning sample storage unit, wherein the generation unit performs the generation process again in a case where a predetermined condition is satisfied.