基于最小分类错误率和Parzen窗的降维方法
기우최소분류착오솔화Parzen창적강유방법
Dimensionality reduction method based on minimum classifica-tion error and Parzen window
  • 万方数据
    计算机工程与应用 계산궤공정여응용
    COMPUTER ENGINEERING AND APPLICATIONS
    2014年 14期 185-188 ,共4页

    贺邓超%郝文宁%陈刚%靳大尉

    하산초%학문저%진강%근대위

    Parzen窗%降维%概率密度%特征选择 Parzen窗%降維%概率密度%特徵選擇
    Parzen창%강유%개솔밀도%특정선택
    Parzen window%dimensionality reduction%density probability%feature selection
    提出了一种基于最小分类错误率和Parzen窗的降维方法，利用Parzen窗估计数据的概率密度分布；通过计算各特征维度下的分类错误率，判断该特征维度对目标分类的贡献度；依据贡献度大小进行特征维度选择从而达到降维的目的。
    제출료일충기우최소분류착오솔화Parzen창적강유방법，이용Parzen창고계수거적개솔밀도분포；통과계산각특정유도하적분류착오솔，판단해특정유도대목표분류적공헌도；의거공헌도대소진행특정유도선택종이체도강유적목적。
    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.
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