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mRMR_0.9_compiled
- Hanchuan Peng, Fuhui Long, and Chris Ding, "Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, No. 8,
mRMR_0.9_compiled
- 利用互信息进行特征抽取的方法实现，能找到最具代表的特征，有效的实现了计算量的减少和可用来维数缩减-The use of mutual information feature extraction method of implementation, to find the most representative characteristics of an effective implementation of the computation of the reduction and can be
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)
mRMR_0.9_compiled
- mRMR_0.9_compiled---mRMR_0.9_compiled---This is a cross-platform version of mimimum-redundancy maximum-relevancy feature selection-mRMR_0.9_compiled---This is a cross-platform version of mimimum-redundancy maximum-relevancy feature selection
mRMR_0.9_compiled
- 按最大相关-最小冗余对特征排序,里面包括求特征间的互信息-Sort the features according to the maximum correlation minimum redundancy
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)
mRMR_0.9_compiled
- mrmr的代码，我也不知道对不对 ，我是下载的，有知道的可以跟我说(MRMR code, I don't know if it's right, I'm downloading it, you know, you can tell me.)