Conditional Random Fields for Labelling Sequential Data in Natural Language Processing
Convert a model built with CRFsuite to an object of class crf
Linear-chain Conditional Random Field
Functionality allowing to tune a crfsuite model using caret
Enrich a data.frame by adding frequently used CRF attributes
Basic classification evaluation metrics for multi-class labelling
Conditional Random Fields parameters
CRF Training data construction: add chunk entity category to a tokenis...
CRF Training data: download training data for doing Named Entity Recog...
Predict the label sequence based on the Conditional Random Field
Extract basic text features which are useful for entity recognition
NA friendly version of sprintf
Wraps the 'CRFsuite' library <https://github.com/chokkan/crfsuite> allowing users to fit a Conditional Random Field model and to apply it on existing data. The focus of the implementation is in the area of Natural Language Processing where this R package allows you to easily build and apply models for named entity recognition, text chunking, part of speech tagging, intent recognition or classification of any category you have in mind. Next to training, a small web application is included in the package to allow you to easily construct training data.