RTM Stacking Results for Machine Translation Performance Prediction
Ergun Biçici · 2019
We obtain new results using referential translation machines with increased number of learning models in the set of results that are stacked to obtain a better mixture of experts prediction.We combine features extracted from the word-level predictions with the sentence-or document-level features, which significantly improve the results on the training sets but decrease the test set results.