evaluate_model

AxModelManager.evaluate_model(sample=None, metric_name=None, fixed_parameters=None)

Evaluate the model over the specified sample.

Parameters:

sampleDataFrame, dict of NDArray or NDArray

containing the data sample where to evaluate the model. If numpy array, it must contain the values of all the model parameters. If DataFrame or dict, it can contain only those parameters to vary. The rest of parameters would be set to the model best point, unless they are further specified using fixed_parameters.

metric_namestr, optional.

Name of the metric to evaluate. If not specified, it will take the first first objective in self.ax_client.

fixed_parametersdict, optional.

A dictionary with structure {param_name: param_val} with the values of the parameters to be fixed in the evaluation. If a given parameter also exists in the sample, the values in the sample will be overwritten by the fixed value.

Returns:

NDArray, NDArray

Two numpy arrays containing the mean of the model and the standard error of the mean (sem), respectively.