saealib.SurrogateAccuracy#

class saealib.SurrogateAccuracy(metrics=<factory>, n_samples=0)[source]#

Bases: object

Container for surrogate accuracy metrics computed after a fit.

Parameters:

  • metrics (dict[str, float])

  • n_samples (int)

metrics#

Mapping from metric name (e.g. "spearman") to scalar value.

Type:

dict[str, float]

n_samples#

Number of training samples used for evaluation.

Type:

int

Methods

__init__

get

Return metric value by name, or default if not present.

Method Details

SurrogateAccuracy.__init__(metrics=<factory>, n_samples=0)#
Parameters:

  • metrics (dict[str, float])

  • n_samples (int)

Return type:

None

SurrogateAccuracy.get(name, default=nan)[source]#

Return metric value by name, or default if not present.

Parameters:

  • name (str)

  • default (float)

Return type:

float