搜索资源列表
mrmr-ftest.zip
- This is a code for feature selection. Which combines minimum redundency and max relevance and Ftest. Originally it is written for gene selection but can be used for any kind of feature selection.,This is a code for feature selection. Which combines m
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
mRMR_0.9_compiled
- mRMR(min-redundancy max-relevance)的matlab程序-matlab program of mRMR(min-redundancy max-relevance)
kl_transform
- KL变换的MATLAB源码程序，用于图形图像地震资料等的处理。效果良好。-KL transform MATLAB source code program for graphic images such as seismic data processing. Good results.
mrmr
- 特征选择的最大相关最小冗余算法，采用信息理论作为度量标准。-Feature selection algorithm for minimum redundancy and maximum correlation, the use of information theory as a metric.
feature_selection
- MRMR和relieff特征选择方法，很经典的，简单易用！-The the MRMR and the relieff feature selection method, very classic, simple and easy to use!
Meta-Biomarker.tar
- meta biomarker code matlab for feature s selection uses filer methods Relief and mrmr with svm and knn like classifier for validation
mRMR
- it is a very good code
mRMR
- mRMR(最小冗余最大相关)的比较好的文档，可参考一下-mRMR (minimum redundancy maximum correlation) of good documentation, reference
FEAST-v1.1.4
- 特征选择工具箱，用于数据特征提取，数据降维包括mRMR等-feature selection toolbox,MItoolbox
mi.0.912
- 该算法用mrmr对支持向量机进行分类 简洁明了 用以理解(The algorithm uses mrmr to classify the support vector machine for simplicity)
mRMR_0.9_compiled
- 最大相关最小冗余的代码，用于对特征进行选择(MRMR feature selection code)
fhgkj-master
- The matlab code mRMR use for feature selection
FSLib_v6.0_2018
- 互信息的MATLAB代码，经典算法MIFS，MRMR等，能正常运行(MI MATLAB code MIFS,MRMR...)
MRMR
- 最小冗余最大关联算法，在预处理数据时非常有用，可提高预测精度，效果很好(Minimum Redundancy maximum correlation algorithm is useful when data preprocessing, can improve prediction accuracy, good results)
feature-selection-mRMR-master
- 特征选择方法，用于降低数据维数，常见的一种特征筛选手段，可以从大量变量中筛选特征变量实现保留变量与目标之间的最大相关性(feature selection method for mRMR)
mRMR And Mutual Information
- 一种基于互信息的非均匀最大相关最小冗余的特征排序算法(Ranking Heterogeneous Features With mRMR And Mutual Information)
mRMR2
- mRMR算法，用于特征选择，包含代码和例子(mRMRalgorithm for feature selection, code and example)
feature-selection-master
- mRMR(最小冗余最大相关)算法，有说明有源码(mRMR (minimum redundancy maximum correlation))
mrmr最大相关
- mrmr最大相关最小冗余，matlab源程序