`edsnlp.metrics.doc_classif`

`DocClassificationMetric`

Multi-head document classification metric.

PARAMETER	DESCRIPTION
`label_attr`	List of Doc._ attributes containing the labels for each head TYPE: `List[str]`
`micro_key`	The key to use to store the micro-averaged results TYPE: `str` DEFAULT: `'micro'`
`macro_key`	The key to use to store the macro-averaged results TYPE: `str` DEFAULT: `'macro'`
`filter_expr`	The filter expression to use to filter the documents TYPE: `Optional[str]` DEFAULT: `None`

Scores multi-head document-level classification (accuracy, precision, recall, F1) for each head.

PARAMETER	DESCRIPTION
`examples`	The examples to score, either a tuple of (golds, preds) or a list of spacy.training.Example objects TYPE: `Union[Tuple[Iterable[Doc], Iterable[Doc]], Iterable[Example]]`
`label_attr`	The list of Doc._ attributes containing the labels for each head TYPE: `List[str]`
`micro_key`	The key to use to store the micro-averaged results TYPE: `str` DEFAULT: `'micro'`
`macro_key`	The key to use to store the macro-averaged results TYPE: `str` DEFAULT: `'macro'`
`filter_expr`	The filter expression to use to filter the documents TYPE: `Optional[str]` DEFAULT: `None`

RETURNS	DESCRIPTION
`Dict[str, Dict[str, Any]]`	Dictionary mapping head names to their respective metrics