explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2025-01-27 01:34:30 +03:00
Code Issues Packages Projects Releases Wiki Activity

Fix formatting [ci skip]

Browse Source
This commit is contained in:
Ines Montani 2020-08-10 00:46:32 +02:00
parent d611cbef43
commit 0832cdd443
1 changed files with 11 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

24
website/docs/api/architectures.md
View File

@ -525,12 +525,11 @@ A neural network model where token vectors are calculated using a CNN. The
vectors are mean pooled and used as features in a feed-forward network. This vectors are mean pooled and used as features in a feed-forward network. This
architecture is usually less accurate than the ensemble, but runs faster. architecture is usually less accurate than the ensemble, but runs faster.
| Name | Type | Description | | Name | Type | Description |
| --------------------------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------- | | ------------------- | ------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `exclusive_classes` | bool | Whether or not categories are mutually exclusive. | | `exclusive_classes` | bool | Whether or not categories are mutually exclusive. |
| `tok2vec` | [`Model`](https://thinc.ai/docs/api-model) | The [`tok2vec`](#tok2vec) layer of the model. | | `tok2vec` | [`Model`](https://thinc.ai/docs/api-model) | The [`tok2vec`](#tok2vec) layer of the model. |
| `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when | | `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when `begin_training` is called. |
| `begin_training` is called. |
### spacy.TextCatBOW.v1 {#TextCatBOW} ### spacy.TextCatBOW.v1 {#TextCatBOW}
@ -548,13 +547,12 @@ architecture is usually less accurate than the ensemble, but runs faster.
An ngram "bag-of-words" model. This architecture should run much faster than the An ngram "bag-of-words" model. This architecture should run much faster than the
others, but may not be as accurate, especially if texts are short. others, but may not be as accurate, especially if texts are short.
| Name | Type | Description | | Name | Type | Description |
| --------------------------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | | ------------------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `exclusive_classes` | bool | Whether or not categories are mutually exclusive. | | `exclusive_classes` | bool | Whether or not categories are mutually exclusive. |
| `ngram_size` | int | Determines the maximum length of the n-grams in the BOW model. For instance, `ngram_size=3`would give unigram, trigram and bigram features. | | `ngram_size` | int | Determines the maximum length of the n-grams in the BOW model. For instance, `ngram_size=3`would give unigram, trigram and bigram features. |
| `no_output_layer` | float | Whether or not to add an output layer to the model (`Softmax` activation if `exclusive_classes=True`, else `Logistic`. | | `no_output_layer` | float | Whether or not to add an output layer to the model (`Softmax` activation if `exclusive_classes=True`, else `Logistic`. |
| `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when | | `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when `begin_training` is called. |
| `begin_training` is called. |
<!-- TODO: <!-- TODO:
### spacy.TextCatLowData.v1 {#TextCatLowData} ### spacy.TextCatLowData.v1 {#TextCatLowData}