Description
Implements Noisy Channel Model Spell Algorithm. Correction candidates are extracted combining context information and word information
How to use
model = ContextSpellCheckerModel.pretrained("spellcheck_clinical","en","clinical/models")
.setInputCols("token")
.setOutputCol("spell")
val model = ContextSpellCheckerModel.pretrained("spellcheck_clinical","en","clinical/models")
.setInputCols("token")
.setOutputCol("spell")
Model Information
| Name: | spellcheck_clinical |
| Type: | ContextSpellCheckerModel |
| Compatibility: | 2.4.2 |
| License: | Licensed |
| Edition: | Official |
| Input labels: | [token] |
| Output labels: | [spell] |
| Language: | en |
| Dependencies: | embeddings_clinical |
Data Source
Trained with PubMed and i2b2 datasets.
PREVIOUSPosology Model