Multiple Nearest Neighbor Algorithm Based on Data Mining

Aimed at the multiple model problem of data mining,the theory and technology of combination model is discussed and the application of combination theory to the nearest neighbor is studied.The paper proposes an algorithm of MNN(multiple nearest neighbor) classifiers using a random subset of attributions.With the simple voting method,the multiple nearest neighbor classifiers are combined via a random attribution set and the output of the multiple NN classifiers is combined.The method of MNN can improve on the classification precision.Comparing the MNN method to NN-ECOC,two strongpoint are obtained:(1)MNN is a more simple method;(2)MNN is not limited by multiple classes.