autointent.metrics.decision_accuracy#

autointent.metrics.decision_accuracy(y_true, y_pred)#

Calculate decision accuracy. Supports both multiclass and multilabel.

The decision accuracy is calculated as:

$$\text{Accuracy}=\frac{\sum _{i=1}^N\mathbb{1}(y_{\text{true},i}=y_{\text{pred},i})}{N}$$

where:

• $N$ is the total number of samples,

• $y_{\text{true},i}$ is the true label for the $i$-th sample,

• $y_{\text{pred},i}$ is the predicted label for the $i$-th sample,

• $\mathbb{1}(\text{condition})$ is the indicator function that equals 1 if the condition

is true and 0 otherwise.

Parameters:

• y_true (autointent.custom_types.ListOfGenericLabels) – True values of labels

• y_pred (autointent.custom_types.ListOfGenericLabels) – Predicted values of labels

Returns:

Score of the decision accuracy

Return type:

float