Weighted KNN Algorithm Based on Random Forests

Huanian Zhang, Fanliang Bu

Abstract: In this paper, we proposed a weighted KNN algorithm based on random forests. The proposed algorithm fully measures the differences in the importance of each feature, and overcomes the shortcoming of k-nearest neighbor (KNN) algorithm in classifying unbalanced data sets and data sets of different feature importance. The classification accuracy of the KNN algorithm is effectively improved, and the performance of the proposed algorithm is verified through experiments.