This algorithm implements standard metrics for biometric system evaluation

This algorithm is a legacy one. The API has changed since its implementation. New versions and forks will need to be updated.
This algorithm is an analyzer. It can only be used on analysis blocks.

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.

Unnamed group

Endpoint Name Data Format Nature
scores elie_khoury/string_probe_scores/1 Input

Analyzers may produce any number of results. Once experiments using this analyzer are done, you may display the results or filter experiments using criteria based on them.

Name Type
threshold float32
far float32
eer float32
roc plot/scatter/1
frr float32
number_of_positives int32
number_of_negatives int32

The code for this algorithm in Python
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This algorithm implements standard metrics for biometric system evaluation.

Specifically, it returns:

  • eer: the equal error rate (EER)
  • far: the false alarm rate (FAR)
  • frr: the false rejection rate (FRR)
  • number_of_positives: the number of positive (genuine) trials
  • number_of_negatives: the number of negative (impostor) trials
  • threshold: the threshold at the equal error rate
  • roc: the receiver operating characteristic (ROC) curve

This implementation relies on the 'measure' package from the Bob library. See http://www.idiap.ch/software/bob/docs/releases/last/sphinx/html/measure/ for more details.

No experiments are using this algorithm.
This algorithm was never executed.
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