Recently, there has been an increased attention in the literature on the use of ensemble methods in multivariate regression and classification. These methods have been shown to have interesting properties both for regression and classification. In particular, they can improve the accuracy of unstable predictors. Ensemble methods have so far, been little studied in situations that are common for...

Ensemble learning is an intensively studies technique in machine learning and pattern recognition. Recent work in computational biology has seen an increasing use of ensemble learning methods due to their unique advantages in dealing with small sample size, high-dimensionality, and complexity data structures. The aim of this article is two-fold. First, it is to provide a review of the most wide...

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 highestperforming 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 close...