A plugin for the GATE language technology framework for training and using machine learning models. Currently supports Mallet (MaxEnt, NaiveBayes, CRF and others), LibSVM, Scikit-Learn, Weka, and DNNs through Pytorch and Keras.
This is probably a result of re-factoring so that the engine now decides on which corpus representation to use. But this means the engine has to know how to initialize the corpus representation.
Instead of passing around yet another parameter in all those methods, the idea is to set the scaling method as part of constructing the feature info or set it once the feature info has been created. The feature info gets passed to the corpus representation, so the scaling info could get set from there.
To make this clear we should remove the constructor parameter for the scaling method alltogether.
This is probably a result of re-factoring so that the engine now decides on which corpus representation to use. But this means the engine has to know how to initialize the corpus representation.
Instead of passing around yet another parameter in all those methods, the idea is to set the scaling method as part of constructing the feature info or set it once the feature info has been created. The feature info gets passed to the corpus representation, so the scaling info could get set from there. To make this clear we should remove the constructor parameter for the scaling method alltogether.