Bob 2.0 implementation of feature projection on a linear machine

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 splittable

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.

Group: asv_real

Endpoint Name Data Format Nature
asv_real_scores elie_khoury/string_probe_scores/1 Input
asv_probe_id system/text/1 Input
fused_scores pkorshunov/fusion_scores/1 Output

Group: pad

Endpoint Name Data Format Nature
pad_scores_class system/text/1 Input
pad_file_id system/text/1 Input
pad_scores system/float/1 Input

Group: asv_attack

Endpoint Name Data Format Nature
asv_attack_scores elie_khoury/string_probe_scores/1 Input
asv_attack_id system/text/1 Input

Unnamed group

Endpoint Name Data Format Nature
classifier tutorial/linear_machine/1 Input

The code for this algorithm in Python
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Project input features on a given linear machine (e.g., logistic regression)

Experiments

Updated Name Databases/Protocols Analyzers
pkorshunov/pkorshunov/isv-asv-pad-fusion-complete/1/asv_isv-pad_lbp_hist_ratios_lr-fusion_lr-pa_aligned avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verification,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train pkorshunov/spoof-score-fusion-roc_hist/1
pkorshunov/pkorshunov/isv-asv-pad-fusion-complete/1/asv_isv-pad_gmm-fusion_lr-pa avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verification,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train pkorshunov/spoof-score-fusion-roc_hist/1

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.

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