A Method for Multi-dimension Data Classification Based on Fuzzy Measure KNN
Bin Deng, Peiji Shao, Mingwu Liu, Guoen Xia · Systems Engineering · 2010
k-nearest neighbor(KNN) algorithm has many advantages such as intuitiveness,requiring no prior knowledge of statistics,unsupervised learning,etc,but it cannot deal effectively with the multi-dimension data sample which uncertainty of sub ordinate relationship due to the fuzziness of boundary element set.This paper presents a fuzzy measures k-Nearest Neighbor(FM-KNN),which applies fuzzy measures to strengthen the quantitative uncertainty characteristic information.The main idea is stated as follows: firstly we use fuzzy measure to solve non-monotonic of Dempster-Shafer Evidence Theory;then we quantify the uncertainty calculation about multi-dimensional attribute information by using of new Dempster-Shafer fuzzy measure function;finally we determine FM-KNN classification rules by a sample of support reliability.The results show that FM-KNN is better than other KNN in the multi-dimensional data classification.