计算机工程与应用Issue(14)：185-188,4.DOI:10.3778/j.issn.1002-8331.1207-0388
基于最小分类错误率和Parzen窗的降维方法
Dimensionality reduction method based on minimum classifica-tion error and Parzen window
贺邓超 1郝文宁 1陈刚 1靳大尉1
作者信息
- 1. 解放军理工大学 工程兵工程学院，南京 210007
- 折叠
摘要
Abstract
A dimensionality reduction method based on minimum classification error and Parzen window is proposed, which firstly uses Parzen window to estimate the probability density of data, then calculates the contribution for classification of each feature dimension with the classification error, and selects the feature dimension according to the contribution for classification, in such a way as to achieve the intention of dimensionality reduction.关键词
Parzen窗/降维/概率密度/特征选择Key words
Parzen window/dimensionality reduction/density probability/feature selection分类
信息技术与安全科学引用本文复制引用
贺邓超,郝文宁,陈刚,靳大尉..基于最小分类错误率和Parzen窗的降维方法[J].计算机工程与应用,2014,(14):185-188,4.
