GateNLP - Learning Framework Plugin
This is the home page for the GateNLP LearningFramework plugin.
The GATE LearningFramework plugin is a plugin for the GATE NLP platform. It supports a number of machine learning tasks relevant to NLP (classification, sequence tagging, topic models, regression) and provides a consistent way to use a broad range of machine learning algorithms from several libraries to perform those tasks.
NOTE: This web site provides the most recent documentation for the plugin. We try to keep the documentation up-to-date with the most recent version of the plugin. The documentation on this web site is mainly intended for users of the LearningFramework. Developer-specific documentation is kept in the GitHub Wiki for the project.
Overview of the documentation:
- Detailed Overview Page - detailed table of contents and pointers to all parts of the documentation
- Installation
- Getting started
- How It Works - a short overview of how things are implemented
- Processing Resources Documentation:
- LF_TrainClassification train a classification model
- LF_ApplyClassification apply a trained classification model
- LF_TrainRegression train a regression model
- LF_ApplyRegression apply a trained regression model
- LF_TrainChunking train a model for sequence tagging / chunking
- LF_ApplyChunking apply a trined model for sequence tagging / chunking
- LF_TrainTopicModel train an LDA topic model
- LF_ApplyTopicModel find topic distribution for new documents/texts
- LF_Export export a training set to an external file
- LF_EvaluateClassification estimate classification accuracy
- LF_EvaluateRegression estimate regression quality
- LF_GenFeatures_Affixes generate features from prefixes and suffixes
- LF_GenFeatures_Misc generate other features like word shape
- Using Neural Networks
- Tutorials
Additional information: