autointent.metrics.regex.regex_partial_precision#
- autointent.metrics.regex.regex_partial_precision(y_true, y_pred)#
Calculate regex partial precision.
The regex partial precision is calculated as:
\[\text{Partial Precision} = \frac{\sum_{i=1}^N \mathbb{1}(y_{\text{true},i} \in y_{\text{pred},i})}{\sum_{i=1}^N \mathbb{1}(|y_{\text{pred},i}| > 0)}\]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,
\(|y_{\text{pred},i}|\) is the number of predicted labels 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.metrics.custom_types.LABELS_VALUE_TYPE) – True values of labels.
y_pred (autointent.metrics.custom_types.LABELS_VALUE_TYPE) – Predicted values of labels.
- Returns:
Score of the regex partial precision.
- Return type: