Ensemble Methods for Native Language Identification
Sophia Chan | Maryam Honari Jahromi | Benjamin Benetti | Aazim Lakhani | Alona Fyshe
Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications
Our team—Uvic-NLP—explored and evaluated a variety of lexical features for Native Language Identification (NLI) within the framework of ensemble methods. Using a subset of the highest performing features, we train Support Vector Machines (SVM) and Fully Connected Neural Networks (FCNN) as base classifiers, and test different methods for combining their outputs. Restricting our scope to the closed essay track in the NLI Shared Task 2017, we find that our best SVM ensemble achieves an F1 score of 0.8730 on the test set.