关键词: 特征选择, 最近邻, 互信息, 邻域互信息

Abstract: Feature selection of neighborhood information system is constrained by the neighborhood size. First, this paper calculates the distance between a given sample and its nearest samples with the same and different labels to define the concept of nearest-neighbor, and determines the size of nearest neighbor simultaneously. Second, the notion of nearest-neighbor is extended to Shannon information theory, and the concept of nearest neighbor mutual information is presented. Then, a forward greedy strategy is used to construct feature selection algorithm based on nearest-neighbor mutual information. Finally, experiments are conducted on eight UCI data sets and two different base classifiers. Experimental results show that the proposed algorithm selects a few features and effectively improves classification performance compared?with other
popular algorithms.

Key words: feature selection, nearest-neighbor, mutual information, neighborhood mutual information