feature-selection-mRMR-master
所属分类：matlab编程
开发工具：matlab
文件大小：10076KB
下载次数：38
上传日期：2018-12-20 01:07:27
上 传 者：
不真实
说明： 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)
文件列表:
dataset (0, 2015-01-16)
dataset\mfeat (0, 2015-01-16)
dataset\mfeat\mfeat-fac (2162000, 2015-01-16)
dataset\mfeat\mfeat-fou (1826000, 2015-01-16)
dataset\mfeat\mfeat-kar (1922000, 2015-01-16)
dataset\mfeat\mfeat-mor (182000, 2015-01-16)
dataset\mfeat\mfeat-pix (1442000, 2015-01-16)
dataset\mfeat\mfeat-zer (1318000, 2015-01-16)
dataset\mfeat\mfeat.info (2442, 2015-01-16)
matlab (0, 2015-01-16)
matlab\+MLpkg (0, 2015-01-16)
matlab\+MLpkg\+dataProcessing (0, 2015-01-16)
matlab\+MLpkg\+dataProcessing\binarize.m (288, 2015-01-16)
matlab\+MLpkg\+featureSelection (0, 2015-01-16)
matlab\+MLpkg\+featureSelection\mRMR.m (1593, 2015-01-16)
matlab\+MLpkg\+mutualInformation (0, 2015-01-16)
matlab\+MLpkg\+mutualInformation\bundleMI.m (349, 2015-01-16)
matlab\+MLpkg\+mutualInformation\mutualInfoDis.m (784, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR (0, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\CmptFeatureMRMR.m (1584, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\compactWrapper.m (2488, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\findCandidateFeature.m (1142, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\plot.m (903, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\prepareData.m (240, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\private (0, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\private\cvErrEst.m (1073, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\set.m (141, 2015-01-16)
matlab\+MLpkg\@CmptFeatureMRMR\setModelPara.m (267, 2015-01-16)
matlab\exampleHDR (0, 2015-01-16)
matlab\exampleHDR\NBback08.eps (14540, 2015-01-16)
matlab\exampleHDR\NBback12.eps (14545, 2015-01-16)
matlab\exampleHDR\NBback50.eps (15939, 2015-01-16)
matlab\exampleHDR\NBfor08.eps (16762, 2015-01-16)
matlab\exampleHDR\NBfor12.eps (16906, 2015-01-16)
matlab\exampleHDR\NBfor50.eps (19163, 2015-01-16)
matlab\exampleHDR\exampleHDR.m (733, 2015-01-16)
matlab\exampleHDR\mfeat.mat (7457733, 2015-01-16)
... ...
feature-selection-mRMR
======================
Feature selection: Minimal Redundancy and Maximal Relevance (mRMR)
### Data set
mfeat: https://archive.ics.uci.edu/ml/datasets/Multiple+Features
### Reference
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,
pp.1226-1238, 2005.
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