Evaluate a pretrained classification model on custom test data.
train_classification
step. Useful to potentially
refit the model on a single dataset split and/or predict samples the model
hasn’t seen before, calculate errors etc., i.e. for sample-based analysis
of model performance.
Examples
ds.first_name
), datasets (ds
or ds[["first_name", "last_name"]]
) or models (referenced
by name e.g. "churn-clf"
).
Inputs
Outputs
step(..., {"param": "value", ...}) -> (output)
.
Parameters
Options
true
, the model will be refit on the train split before evaluation. If set to false
,
the model will be evaluated on the test split without refitting. If no split
configuration is provided,
this parameter is ignored.