Docs / Models
Inputs and outputs
What goes into a model card and what comes out.
Inputs
Usually Epochs, sometimes Raw or a
Table of features. The manifest declares which, and the type check
refuses the wrong one before anything runs.
Shape matters
A model trained on 64 channels at 256 Hz will accept 128 channels at 1024 Hz without complaining and return nonsense. Model cards should declare their expected sampling rate and channel count as parameters, and refuse when they do not match.
If a model card you install does not check this, that is
worth reporting to its author. Silent acceptance of the wrong shape is the most
common way a model produces a confident wrong answer.
Outputs
Table | One row per trial or per channel, with the prediction and usually a confidence |
|---|---|
Matrix | Channel by channel, for connectivity or similarity models |
Epochs | When the model transforms rather than classifies |
On confidence values
A confidence is a number the model produces, not a probability that it is right. Treat it as a ranking, not as a calibrated measure, unless the author says otherwise and shows the calibration.