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所属分类Windows2018无需申请注册送58体验金
开发工具:matlab
文件2018注册送白菜网:3KB
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上传日期:2020-08-02 12:02:20
上 传 者gegegeer
说明:  采用特征子集的Bhattacharyya距离作为浮动顺序搜索算法的评价函数,评估特征子集对样本分类的贡献,即: 其中表示具有i个基因的特征子集的Bhattacharyya距离。和为特征子集的基因在正常和患有肝癌两个样本中表达的均值向量,和为对应的协方差矩阵。令为含有i个基因的特征子集中具有最大评价函数值的基因集合,它表示所有维数为i的特征基因子集中对分类贡献最大的基因集合。利用浮动顺序搜索算法在特征子集空间中进行搜索,得到具有不同维数的候选特征子集。
(The Bhattacharyya distance of feature subset is used as the evaluation function of floating order search algorithm to evaluate the contribution of feature subset to sample classification Where represents the Bhattacharyya distance of the characteristic subset with I genes. The sum of the mean vectors of genes with feature subsets in normal and HCC samples is the corresponding covariance matrix. Let it be the gene set with the largest evaluation function value in the feature subset containing I genes, which represents the gene set with the largest contribution to the classification of all feature gene subsets with dimension I. The floating order search algorithm is used to search in the feature subset space, and candidate feature subsets with different dimensions are obtained,)

文件列表:[举报垃圾]
FFSA.m, 4942 , 2020-08-01
Test_PNN_Optimal.m, 1998 , 2020-08-02
Bt.m, 658 , 2020-08-01

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2018无需申请注册送58体验金