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 |
|---|---|---|
| comparison_ids | system/array_1d_text/1 | Input |
| keystroke | tutorial/atvs_keystroke/1 | Input |
| probe_client_id | system/text/1 | Input |
| scores | elie_khoury/string_probe_scores/1 | Output |
| Endpoint Name | Data Format | Nature |
|---|---|---|
| template_client_id | system/text/1 | Input |
| id | system/text/1 | Input |
| features | tutorial/atvs_keystroke/1 | Input |
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
| Name | Description | Type | Default | Range/Choices |
|---|---|---|---|---|
| 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 |
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.
Note
All features must have the same length.
| Updated | Name | Databases/Protocols | Analyzers | |||
|---|---|---|---|---|---|---|
| robertodaza/robertodaza/example2/2/article-block-all1 | atvskeystroke/1@A | robertodaza/analyzerahora/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.