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mr-runk
- 基于互信息理论的最大相关排序算法，可应用于各领域的特征选择。-Maximum mutual information based relevance ranking algorithm theory can be applied to all areas of feature selection.
mRMRFeatureSelection
- mRMR_0.9_compiled最小冗余和最大相关特征选取源代码，-This package is the mRMR (minimum-redundancy maximum-relevancy) feature selection method, whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent pu
tezhengxuanzhe
- 利用最小互信息实现向量的特征选择，优化分类器的设计，原创-The use of mutual information to achieve the smallest feature selection vectors, optimizing the classifier design, originality
IEEEXplore-4.pdf
- Mutual Information Feature Selection
LSFS
- 有监督的特征选择和优化程序MATLAB代码，基于最小二乘算法。内有测试数据，和详细程序说明-Least-Squares Feature Selection (LSFS) is a feature selection method for supervised regression and classification. LSFS orders input features according to their dependence on output values. Dependency bet
Matlabcode
- 粗糙集代码 data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set based feature evaluation and selection -Rough code data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set bas
neighborhood-mu-info
- 基于邻里互信息特征的评价与选择,数据挖掘，Matlab平台-neighborhood mutual information based feature uation and selection
feature-selection-master
- 最小冗余最大相关性（MRMR）（MRMR.M） 需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱 偏最小二乘（PLS）回归系数（ReGCOEF.m） 使用MATLAB统计工具箱中的PLSReress ReliefF（分类）和RReliefF（回归）（ReleFracePr.M.） 从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。 ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA