Combining feature extraction and expansion to improve classification based similarity learning.

•A competitive similarity learning method using a classification setting is proposed.•The format of the data input has a major influence in classification performance.•Best results are obtained by combining feature extraction and expansion.•Adding a set of convenient standard distances help learning of the similarity score.•Results are above state-of-the-art metric learning methods in a variety of contexts.