Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Abstract. Ensemble methods allow to improve the accuracy of classification methods. This work considers the application of one of these methods, named Rotation-based, when the clas...
Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with ...
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on gen...
We present a new ensemble learning method that employs a set of regional classifiers, each of which learns to handle a subset of the training data. We split the training data and ...