`edsnlp.scorers.span_attributes`

`span_attribute_scorer`

Scores the attributes predictions between a list of gold and predicted spans.

PARAMETER	DESCRIPTION
`args`	The examples to score, either a tuple of (golds, preds) or a list of spacy.training.Example objects TYPE: `Examples`
`span_getter`	The span getter to use to extract the spans from the document TYPE: `SpanGetterArg`
`attributes`	The attributes to use to score the spans TYPE: `Sequence[str]`
`default_values`	Values to dismiss when computing the micro-average per label. This is useful to compute precision and recall for certain attributes that have imbalanced value repartitions, such as "negation", "family related" or "certainty" attributes. TYPE: `Dict` DEFAULT: `{}`
`include_falsy`	Whether to count predicted or gold occurrences of falsy values when computing the metrics. If `False`, only the non-falsy values will be counted and matched together. TYPE: `bool` DEFAULT: `False`
`micro_key`	The key to use to store the micro-averaged results for spans of all types TYPE: `str` DEFAULT: `'micro'`
`filter_expr`	The filter expression to use to filter the documents TYPE: `Optional[str]` DEFAULT: `None`

RETURNS	DESCRIPTION
`Dict[str, float]`