### algorithms tutorial linear_machines_scoring 3

Minimum Euclidean distance comparison against a template matrix

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: probes

Endpoint Name Data Format Nature
probe_projections system/array_2d_floats/1 Input
comparison_ids system/array_1d_uint64/1 Input
probe_id system/uint64/1 Input
probe_client_id system/uint64/1 Input
scores tutorial/probe_scores/1 Output

#### Group: templates

Endpoint Name Data Format Nature
template_client_id system/uint64/1 Input
template_id system/uint64/1 Input
template_projections system/array_2d_floats/1 Input

The code for this algorithm in Python
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This algorithm generates comparison scores between test samples and matrix templates. Comparisons are performed using the Euclidean distance. As a score, the negation of the minimum distance between the row test (probe) vectors and the row vectors from the template matrix is returned.

The inputs are:

• probe_projections: a two-dimensional arrays of float (64 bits)
representing the (row) test vectors (the number of test vectors corresponds to the number of rows of the matrix)
• comparison_ids: a list of id (as an unsigned 64 bit integers) of
of template/models against which to compare the given probe
• probe_id: an identifier (as an unsigned 64 bit integers) for the
given probe
• probe_client_id: an identifier (as an unsigned 64 bit integers) for
the client from which this probe samples was generated.
• template_client_id: an identifier (as an unsigned 64 bit integers) for
the client from which this template was generated.
• template_id: an identifier (as an unsigned 64 bit integers) for the
given template
• tempalate_projections: a two-dimensional arrays of float (64 bits)
representing the template matrix

The output scores is the corresponding set of score values.

#### Experiments

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.