Metric Functions#

Functions used for Metrics

Overview Information Here: boa.metrics

boa.metrics.metric_funcs.normalized_root_mean_squared_error(y_true, y_pred, normalizer='iqr', **kwargs)[source]#

Normalized root mean squared error

Parameters

  • y_true (array_like) – With shape (n_samples,) or (n_samples, n_outputs) Ground truth (correct) target values.

  • y_pred (array_like) – With shape (n_samples,) or (n_samples, n_outputs) Estimated target values.

  • normalizer (str) – How to normalize the RMSE, options include iqr, std, mean, and range. (default iqr)

  • **kwargs – see sklearn.metrics.mean_squared_error for additional options

Returns

nrmse – A normalized version of RMSE

Return type

float or numpy.ndarray[float]

boa.metrics.metric_funcs.setup_sklearn_metric(metric_to_eval, instantiate=True, **kw)[source]#
boa.metrics.metric_funcs.get_sklearn_func(metric_to_eval)[source]#