mirror of https://github.com/explosion/spaCy.git
65 lines
4.5 KiB
Markdown
65 lines
4.5 KiB
Markdown
---
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title: Scorer
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teaser: Compute evaluation scores
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tag: class
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source: spacy/scorer.py
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---
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The `Scorer` computes and stores evaluation scores. It's typically created by
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[`Language.evaluate`](/api/language#evaluate).
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## Scorer.\_\_init\_\_ {#init tag="method"}
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Create a new `Scorer`.
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> #### Example
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>
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> ```python
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> from spacy.scorer import Scorer
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>
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> scorer = Scorer()
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> ```
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| Name | Type | Description |
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| ------------ | -------- | ------------------------------------------------------------ |
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| `eval_punct` | bool | Evaluate the dependency attachments to and from punctuation. |
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| **RETURNS** | `Scorer` | The newly created object. |
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## Scorer.score {#score tag="method"}
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Update the evaluation scores from a single [`Doc`](/api/doc) /
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[`GoldParse`](/api/goldparse) pair.
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> #### Example
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>
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> ```python
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> scorer = Scorer()
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> scorer.score(doc, gold)
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> ```
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| Name | Type | Description |
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| -------------- | ----------- | -------------------------------------------------------------------------------------------------------------------- |
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| `doc` | `Doc` | The predicted annotations. |
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| `gold` | `GoldParse` | The correct annotations. |
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| `verbose` | bool | Print debugging information. |
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| `punct_labels` | tuple | Dependency labels for punctuation. Used to evaluate dependency attachments to punctuation if `eval_punct` is `True`. |
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## Properties
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| Name | Type | Description |
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| --------------------------------------------------- | ----- | ---------------------------------------------------------------------------------------------------------- |
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| `token_acc` | float | Tokenization accuracy. |
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| `tags_acc` | float | Part-of-speech tag accuracy (fine grained tags, i.e. `Token.tag`). |
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| `uas` | float | Unlabelled dependency score. |
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| `las` | float | Labelled dependency score. |
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| `ents_p` | float | Named entity accuracy (precision). |
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| `ents_r` | float | Named entity accuracy (recall). |
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| `ents_f` | float | Named entity accuracy (F-score). |
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| `ents_per_type` <Tag variant="new">2.1.5</Tag> | dict | Scores per entity label. Keyed by label, mapped to a dict of `p`, `r` and `f` scores. |
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| `textcat_f` <Tag variant="new">3.0</Tag> | float | F-score on positive label for binary classification, macro-averaged F-score otherwise. |
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| `textcat_auc` <Tag variant="new"3.0</Tag> | float | Macro-averaged AUC ROC score for multilabel classification (`-1` if undefined). |
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| `textcats_f_per_cat` <Tag variant="new">3.0</Tag> | dict | F-scores per textcat label, keyed by label. |
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| `textcats_auc_per_cat` <Tag variant="new">3.0</Tag> | dict | ROC AUC scores per textcat label, keyed by label. |
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| `las_per_type` <Tag variant="new">2.2.3</Tag> | dict | Labelled dependency scores, keyed by label. |
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| `scores` | dict | All scores, keyed by type. |
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