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Update textcat API docs

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This commit is contained in:
Adriane Boyd 2022-10-25 15:30:51 +02:00
parent 7b139d1bcd
commit a36891ac4e
2 changed files with 7 additions and 7 deletions
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9
spacy/pipeline/textcat.py
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@ -72,7 +72,7 @@ subword_features = true
"textcat",
assigns=["doc.cats"],
default_config={
"threshold": 0.0,
"threshold": None,
"model": DEFAULT_SINGLE_TEXTCAT_MODEL,
"scorer": {"@scorers": "spacy.textcat_scorer.v1"},
},
@ -94,7 +94,7 @@ def make_textcat(
nlp: Language,
name: str,
model: Model[List[Doc], List[Floats2d]],
threshold: float,
threshold: Optional[float],
scorer: Optional[Callable],
) -> "TextCategorizer":
"""Create a TextCategorizer component. The text categorizer predicts categories
@ -135,7 +135,7 @@ class TextCategorizer(TrainablePipe):
model: Model,
name: str = "textcat",
*,
threshold: float,
threshold: Optional[float],
scorer: Optional[Callable] = textcat_score,
) -> None:
"""Initialize a text categorizer for single-label classification.
@ -144,7 +144,8 @@ class TextCategorizer(TrainablePipe):
model (thinc.api.Model): The Thinc Model powering the pipeline component.
name (str): The component instance name, used to add entries to the
losses during training.
threshold (float): Cutoff to consider a prediction "positive".
threshold (Optional[float]): Unused, not needed for single-label
(exclusive classes) classification.
scorer (Optional[Callable]): The scoring method. Defaults to
Scorer.score_cats for the attribute "cats".

5
website/docs/api/textcategorizer.md
View File

@ -63,7 +63,6 @@ architectures and their arguments and hyperparameters.
> ```python
> from spacy.pipeline.textcat import DEFAULT_SINGLE_TEXTCAT_MODEL
> config = {
> "threshold": 0.5,
> "model": DEFAULT_SINGLE_TEXTCAT_MODEL,
> }
> nlp.add_pipe("textcat", config=config)
@ -82,7 +81,7 @@ architectures and their arguments and hyperparameters.
| Setting | Description |
| ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `threshold` | Cutoff to consider a prediction "positive", relevant when printing accuracy results. ~~float~~ |
| `threshold` | Cutoff to consider a prediction "positive", relevant for `textcat_multilabel` when calculating accuracy scores. ~~float~~ |
| `model` | A model instance that predicts scores for each category. Defaults to [TextCatEnsemble](/api/architectures#TextCatEnsemble). ~~Model[List[Doc], List[Floats2d]]~~ |
| `scorer` | The scoring method. Defaults to [`Scorer.score_cats`](/api/scorer#score_cats) for the attribute `"cats"`. ~~Optional[Callable]~~ |
@ -123,7 +122,7 @@ shortcut for this and instantiate the component using its string name and
| `model` | The Thinc [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model[List[Doc], List[Floats2d]]~~ |
| `name` | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
| _keyword-only_ | |
| `threshold` | Cutoff to consider a prediction "positive", relevant when printing accuracy results. ~~float~~ |
| `threshold` | Cutoff to consider a prediction "positive", relevant for `textcat_multilabel` when calculating accuracy scores. ~~float~~ |
| `scorer` | The scoring method. Defaults to [`Scorer.score_cats`](/api/scorer#score_cats) for the attribute `"cats"`. ~~Optional[Callable]~~ |
## TextCategorizer.\_\_call\_\_ {#call tag="method"}