Commit Graph

21 Commits

Author SHA1 Message Date
Adriane Boyd
507422149f
Various docs updates for v3.0 (#8353)
* Update cats score names in Scorer API docs

* Refer to performance in meta

* Update package naming/versions, lemmatizer details

* Minor formatting fixes

* Provide more explanation for cats_score_desc

* Provide language-specific lemmatizer defaults in API docs

Co-authored-by: Paul O'Leary McCann <polm@dampfkraft.com>
2021-06-14 12:19:36 +02:00
Sofie Van Landeghem
204c2f116b
Extend score_spans for overlapping & non-labeled spans (#7209)
* extend span scorer with consider_label and allow_overlap

* unit test for spans y2x overlap

* add score_spans unit test

* docs for new fields in scorer.score_spans

* rename to include_label

* spell out if-else for clarity

* rename to 'labeled'

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
2021-04-08 12:19:17 +02:00
svlandeg
248339039e fix type in docs 2021-02-26 14:27:10 +01:00
Adriane Boyd
a4b32b9552
Handle missing reference values in scorer (#6286)
* Handle missing reference values in scorer

Handle missing values in reference doc during scoring where it is
possible to detect an unset state for the attribute. If no reference
docs contain annotation, `None` is returned instead of a score. `spacy
evaluate` displays `-` for missing scores and the missing scores are
saved as `None`/`null` in the metrics.

Attributes without unset states:

* `token.head`: relies on `token.dep` to recognize unset values
* `doc.cats`: unable to handle missing annotation

Additional changes:

* add optional `has_annotation` check to `score_scans` to replace
`doc.sents` hack
* update `score_token_attr_per_feat` to handle missing and empty morph
representations
* fix bug in `Doc.has_annotation` for normalization of `IS_SENT_START`
vs. `SENT_START`

* Fix import

* Update return types
2020-11-03 15:47:18 +01:00
Sofie Van Landeghem
75a202ce65
TextCat updates and fixes (#6263)
* small fix in example imports

* throw error when train_corpus or dev_corpus is not a string

* small fix in custom logger example

* limit macro_auc to labels with 2 annotations

* fix typo

* also create parents of output_dir if need be

* update documentation of textcat scores

* refactor TextCatEnsemble

* fix tests for new AUC definition

* bump to 3.0.0a42

* update docs

* rename to spacy.TextCatEnsemble.v2

* spacy.TextCatEnsemble.v1 in legacy

* cleanup

* small fix

* update to 3.0.0rc2

* fix import that got lost in merge

* cursed IDE

* fix two typos
2020-10-18 14:50:41 +02:00
Sofie Van Landeghem
c7eedd3534
updates to NEL functionality (#6132)
* NEL: read sentences and ents from reference

* fiddling with sent_start annotations

* add KB serialization test

* KB write additional file with strings.json

* score_links function to calculate NEL P/R/F

* formatting

* documentation
2020-09-24 16:53:59 +02:00
Ines Montani
3ae5e02f4f Update docs, types and API consistency 2020-08-17 16:45:24 +02:00
Ines Montani
5a221f79c2 Revert "Remove keyword-only from Scorer API docs" [ci skip]
This reverts commit 7a6ac47dc1.
2020-07-31 14:00:21 +02:00
Adriane Boyd
9d79916792 Merge branch 'develop' into feature/scorer-adjustments 2020-07-31 10:48:14 +02:00
Ines Montani
e0ffe36e79 Update docstrings, docs and types 2020-07-29 11:36:42 +02:00
Adriane Boyd
7a6ac47dc1 Remove keyword-only from Scorer API docs 2020-07-29 10:40:30 +02:00
Ines Montani
ac24adec73 Small adjustments to Scorer and docs 2020-07-28 21:39:42 +02:00
Adriane Boyd
fdf09cb231 Update Scorer API docs for score_cats 2020-07-27 15:34:42 +02:00
Adriane Boyd
2bcceb80c4
Refactor the Scorer to improve flexibility (#5731)
* Refactor the Scorer to improve flexibility

Refactor the `Scorer` to improve flexibility for arbitrary pipeline
components.

* Individual pipeline components provide their own `evaluate` methods
that score a list of `Example`s and return a dictionary of scores
* `Scorer` is initialized either:
  * with a provided pipeline containing components to be scored
  * with a default pipeline containing the built-in statistical
    components (senter, tagger, morphologizer, parser, ner)
* `Scorer.score` evaluates a list of `Example`s and returns a dictionary
of scores referring to the scores provided by the components in the
pipeline

Significant differences:

* `tags_acc` is renamed to `tag_acc` to be consistent with `token_acc`
and the new `morph_acc`, `pos_acc`, and `lemma_acc`
* Scoring is no longer cumulative: `Scorer.score` scores a list of
examples rather than a single example and does not retain any state
about previously scored examples
* PRF values in the returned scores are no longer multiplied by 100

* Add kwargs to Morphologizer.evaluate

* Create generalized scoring methods in Scorer

* Generalized static scoring methods are added to `Scorer`
  * Methods require an attribute (either on Token or Doc) that is
used to key the returned scores

Naming differences:

* `uas`, `las`, and `las_per_type` in the scores dict are renamed to
`dep_uas`, `dep_las`, and `dep_las_per_type`

Scoring differences:

* `Doc.sents` is now scored as spans rather than on sentence-initial
token positions so that `Doc.sents` and `Doc.ents` can be scored with
the same method (this lowers scores since a single incorrect sentence
start results in two incorrect spans)

* Simplify / extend hasattr check for eval method

* Add hasattr check to tokenizer scoring
* Simplify to hasattr check for component scoring

* Reset Example alignment if docs are set

Reset the Example alignment if either doc is set in case the
tokenization has changed.

* Add PRF tokenization scoring for tokens as spans

Add PRF scores for tokens as character spans. The scores are:

* token_acc: # correct tokens / # gold tokens
* token_p/r/f: PRF for (token.idx, token.idx + len(token))

* Add docstring to Scorer.score_tokenization

* Rename component.evaluate() to component.score()

* Update Scorer API docs

* Update scoring for positive_label in textcat

* Fix TextCategorizer.score kwargs

* Update Language.evaluate docs

* Update score names in default config
2020-07-25 12:53:02 +02:00
svlandeg
2b60e894cb fix component constructors, update, begin_training, reference to GoldParse 2020-07-07 19:17:19 +02:00
Ines Montani
18a900abc2 Fix markup 2020-07-01 13:02:07 +02:00
Sofie Van Landeghem
c0f4a1e43b
train is from-config by default (#5575)
* verbose and tag_map options

* adding init_tok2vec option and only changing the tok2vec that is specified

* adding omit_extra_lookups and verifying textcat config

* wip

* pretrain bugfix

* add replace and resume options

* train_textcat fix

* raw text functionality

* improve UX when KeyError or when input data can't be parsed

* avoid unnecessary access to goldparse in TextCat pipe

* save performance information in nlp.meta

* add noise_level to config

* move nn_parser's defaults to config file

* multitask in config - doesn't work yet

* scorer offering both F and AUC options, need to be specified in config

* add textcat verification code from old train script

* small fixes to config files

* clean up

* set default config for ner/parser to allow create_pipe to work as before

* two more test fixes

* small fixes

* cleanup

* fix NER pickling + additional unit test

* create_pipe as before
2020-06-12 02:02:07 +02:00
Ines Montani
a6200bc424 Update scorer.md [ci skip] 2019-11-21 17:02:43 +01:00
adrianeboyd
b5d999e510 Add textcat to train CLI (#4226)
* Add doc.cats to spacy.gold at the paragraph level

Support `doc.cats` as `"cats": [{"label": string, "value": number}]` in
the spacy JSON training format at the paragraph level.

* `spacy.gold.docs_to_json()` writes `docs.cats`

* `GoldCorpus` reads in cats in each `GoldParse`

* Update instances of gold_tuples to handle cats

Update iteration over gold_tuples / gold_parses to handle addition of
cats at the paragraph level.

* Add textcat to train CLI

* Add textcat options to train CLI
* Add textcat labels in `TextCategorizer.begin_training()`
* Add textcat evaluation to `Scorer`:
  * For binary exclusive classes with provided label: F1 for label
  * For 2+ exclusive classes: F1 macro average
  * For multilabel (not exclusive): ROC AUC macro average (currently
relying on sklearn)
* Provide user info on textcat evaluation settings, potential
incompatibilities
* Provide pipeline to Scorer in `Language.evaluate` for textcat config
* Customize train CLI output to include only metrics relevant to current
pipeline
* Add textcat evaluation to evaluate CLI

* Fix handling of unset arguments and config params

Fix handling of unset arguments and model confiug parameters in Scorer
initialization.

* Temporarily add sklearn requirement

* Remove sklearn version number

* Improve Scorer handling of models without textcats

* Fixing Scorer handling of models without textcats

* Update Scorer output for python 2.7

* Modify inf in Scorer for python 2.7

* Auto-format

Also make small adjustments to make auto-formatting with black easier and produce nicer results

* Move error message to Errors

* Update documentation

* Add cats to annotation JSON format [ci skip]

* Fix tpl flag and docs [ci skip]

* Switch to internal roc_auc_score

Switch to internal `roc_auc_score()` adapted from scikit-learn.

* Add AUCROCScore tests and improve errors/warnings

* Add tests for AUCROCScore and roc_auc_score
* Add missing error for only positive/negative values
* Remove unnecessary warnings and errors

* Make reduced roc_auc_score functions private

Because most of the checks and warnings have been stripped for the
internal functions and access is only intended through `ROCAUCScore`,
make the functions for roc_auc_score adapted from scikit-learn private.

* Check that data corresponds with multilabel flag

Check that the training instances correspond with the multilabel flag,
adding the multilabel flag if required.

* Add textcat score to early stopping check

* Add more checks to debug-data for textcat

* Add example training data for textcat

* Add more checks to textcat train CLI

* Check configuration when extending base model
* Fix typos

* Update textcat example data

* Provide licensing details and licenses for data
* Remove two labels with no positive instances from jigsaw-toxic-comment
data.


Co-authored-by: Ines Montani <ines@ines.io>
2019-09-15 22:31:31 +02:00
Ines Montani
8721849423 Update Scorer.ents_per_type 2019-07-10 11:19:28 +02:00
Ines Montani
b78a8dc1d2 Update Scorer and add API docs 2019-05-24 14:06:04 +02:00