Forked from robertodaza/prueba1/3
|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|
Algorithms may use functions and classes
declared in libraries. Here you can see the libraries and
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lib, then access function
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This algorithm is designed to be used as a simple enrollment strategy of keystroke data. It enrolls a model from several features by computing the average and standard deviation of the enrollment features.
All features must have the same length.
This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.