A New Ensemble Learning Method Embedded with PCA-ReliefF Algorithm

Abstract

Improving the generalization ability of ensemble learning is very important. This paper proposes a new ensemble learning method embedded with PCA-ReliefF Algorithm. It can efficiently remove the influence of noise features, and improve the classification accuracy of ensemble learning. Experiments on UCI dataset show that the method in this paper is feasible and effective, and provides a new research approach for feature classification in pattern recognition.