Relearning Ensemble Selection Based on New Generated Features

The ensemble methods are meta-algorithms that combine several base machine learning techniques to increase the effectiveness of classification. Many existing committees classifiers use classifier selection process determine optimal set classifiers. In this article, we propose framework with relearning Additionally, in proposed newly generated features, which can be obtained after process. technique was compared state-of-the-art using three benchmark datasets and one synthetic dataset. Four classification performance measures used evaluate method.