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USPEX is a crystal structure predictor based on an evolutionary algorithm. Every USPEX run produces hundreds or thousands of crystal structures, some of which may be identical. To ease the extraction of unique and potentially interesting structures we applied usual high-dimensional classification concepts to the unusual field of crystallography. We experimented with various crystal structure descriptors, distinct distance measures and tried different clustering methods to identify groups of similar structures. These methods are already applied in combinatorial chemistry to organic molecules for a different goal and in somewhat different forms, but are not widely used for crystal structures classification. We adopted a visual design and validation method in the development of a library (CrystalFp) and an end-user application to select and validate method choices, to gain userspsila acceptance and to tap into their domain expertise. The use of the classifier has already accelerated the analysis of USPEX output by at least one order of magnitude, promoting some new crystallographic insight and discovery. Furthermore the visual display of key algorithm indicators has led to diverse, unexpected discoveries that will improve the USPEX algorithms.