A quick evidential classification algorithm based on k-nearest neighbor rule

Under the frame of Dempster-Shafer theory of evidence, a distance function to depict comparability between evidences is constructed according to the conflict among evidences, which is for the case that the origin of few evidences is uncertain. In order to conquer these disadvantages of traditional quick k-nearest neighbor (k-NN) classification algorithm, this paper proposes a quick k-NN evidence classification algorithm-super-ball search evidence classification (ab. S-BSEC) algorithm based on near neighbor searching. Simulation results show that this method is superior to the traditional k-NN algorithm in terms of the recognition speed under the same recognition rate and k, and super-ball algorithm is not sensitive to searching order of training sample.