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Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.
|Endpoint Name||Data Format||Nature|
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
|field||Data field used to generate the feature template||string||given_name||given_name, family_name, email, nationality, id_number, all_five|
|distance||Distance to obtain the matching score||string||Modified Scaled Manhattan||Scaled Manhattan, Modified Scaled Manhattan, Combined Manhattan-Mahalanobis, Mahalanobis + Nearest Neighbor|
The code for this algorithm in Python
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For a given set of feature vectors and enrollment set, the modified manhattan scaled distance is obtained. See  for details.
AGREEMENT ON THE USE OF THIS CODE AND ANY GENERATED DATA
 A. Morales, M. Falanga, J. Fierrez, C. Sansone and J. Ortega-Garcia, "Keystroke Dynamics Recognition based on Personal Data: A Comparative Experimental Evaluation Implementing Reproducible Research ", in Proc. the IEEE Seventh International Conference on Biometrics: Theory, Applications and Systems, Arlington, Virginia, USA, September 2015