hosa.models.cnn.cnn_models.CNNClassification.score

CNNClassification.score(x, y, imbalance_correction=False, **kwargs)[source]

Computes the performance metrics on the given input data and target values.

Parameters

  • x (numpy.ndarray) – Input data.

  • y (numpy.ndarray) – Target values (i.e., class labels).

  • imbalance_correction (bool) – True if correction for imbalance should be applied to the metrics; False otherwise.

  • **kwargs – Ignored. Only included here for compatibility’s sake.

Returns

tuple –

Returns a tuple containing the area under the ROC curve (AUC), accuracy,

sensitivity, and sensitivity.

Note

This function can be used for both binary and multiclass classification.