Nonparametric Feature Selection Method Based on Local Interclass Structure
Nonparametric Feature Selection Method Based on Local Interclass Structure
复制标题
基于局部类间结构的非参数特征选择方法
DOI：
10.1109/tsmc.1981.4308675
复制
发表时间：
1981
期刊：
影响因子：
--
通讯作者：
M. Ichino
中科院分区：
文献类型：
--
作者：
M. Ichino
提出了一种适用于混合特征模式识别问题的非参数特征选择方法。在模式空间中，每个模式类根据局部类间结构由多个子区域表示。然后在每个子区域中，以简单的非参数方式执行特征选择。我们的特征选择方法可以选择一个特征子集的基础上，高阶判别信息。我们的方法的一些基本性质的理论和实验。
A nonparametric feature selection method which can be applicable to pattern recognition problems based on mixed features is presented. In the pattern space, each pattern class is represented by multiple subregions according to local interclass structure. Then in each of the subregions, feature selection is performed in a simple nonparametric way. Our feature selection method can select a feature subset based on higher order discriminating information. Some basic properties of our approach are presented theoretically and experimentally.