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Biometric identification systems build features, which describe people, using various data. Usually it is not known which of features could be chosen, and a dedicated process called a feature selection is applied to resolve this uncertainty. The relevant features, that are selected with this process, then describe the people in the system as well as possible. It is likely that the relevancy of selected features also mean that these features describe the important things in the measured behavior and that they partly reveal how the behavior works. This paper uses this idea and evaluates results of many runs of feature selection runs in a system, that identifies people using their moving a computer mouse. It has been found that the most frequently selected features repeat between runs, and that these features describe the similar things of the movements. © 2016 Author(s)

Features preferred in-identification system based on computer mouse movements