Version: 0.5.x

metrics

Utility functions for measuring accuracy and performance.

Module: aisp.utils.metrics
Import: from aisp.utils import metrics

Functions

def accuracy_score(
    y_true: Union[npt.NDArray, list],
    y_pred: Union[npt.NDArray, list]
) -> float:
    ...

Calculate the accuracy score based on true and predicted labels.

Parameters

Name	Type	Default	Description
`y_true`	`Union[npt.NDArray, list]`	-	Ground truth (correct) labels. Expected to be of the same length as `y_pred`.
`y_pred`	`Union[npt.NDArray, list]`	-	Predicted labels. Expected to be of the same length as `y_true`.

Returns

Type	Description
`float`	The ratio of correct predictions to the total number of predictions.

Raises

Exception	Description
`ValueError`	If `y_true` or `y_pred` are empty or if they do not have the same length.