Face Recognition Using Bagging Knn

In this paper a novel ensemble based techniques for face recognition is presented. In ensemble learning a group of methods are employed and their results are combined to form the final results of the system. Gaining the higher accuracy rate is the main advantage of this system. Two of the most successful wrapping classification methods are bagging and boosting. In this paper we used the K nearest neighbors (kNN) as the main classification technique and Bagging as the wrapping classification methods. The results of these setting for the ORL face database are reported.