Matlabcode Rough code data reduction with fuzzy ro

Title: Matlabcode

Category:
Mathimatics-Numerical algorithms
Tags:
[Matlab] [源码]
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38kb
Update:
2012-11-26
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jishiyugq326102

Description: Rough code data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set based feature evaluation and selection

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To Search: FEATURE SELECTION Rough set mutual information feature selection fuzzy rough set matlab code fuzzy rough sets feature matlab fuzzy rough set feature selection feature selection rough set

[gray-pid] - gray pid, discrete gray, gray row, pid c
[@linear] - Normal feature selection for SVM algorit
[best] - rough set materials using java
[Verver_FS_Version_5.1.6] - Feature Selection using matlab
[@fsv] - feature selection based of Forwad search
[ACO] - aco feature selection
[rsar_1.3.3.tar] - sar is a Rough Set-based Attribute Reduc
[datareduct] - data reduction with fuzzy rough sets or
[codeofroughset] - Rough set theory is a new mathematical a
[roughsets] - rough set matlab program

File list (Check if you may need any files):

Matlab code of rough set
........................\data reduction with fuzzy rough sets or fuzzy mutual information
........................\................................................................\demo.m
........................\................................................................\entropy.m
........................\................................................................\entropy_interval.m
........................\................................................................\fs_con_N.m
........................\................................................................\fs_entropy.asv
........................\................................................................\fs_entropy.m
........................\................................................................\fs_neighbor.asv
........................\................................................................\fs_neighbor.m
........................\................................................................\kersim.m
........................\................................................................\kersim_crisp.m
........................\................................................................\wine.mat
........................\fuzzy preference rough set based feature evaluation and selection
........................\.................................................................\FGC.m
........................\.................................................................\FLC.m
........................\.................................................................\FS_PL_FRS.m
........................\.................................................................\FS_PL_RS.m
........................\.................................................................\FUC.m
........................\.................................................................\GC.m
........................\.................................................................\LC.m
........................\.................................................................\UC.m
........................\kernelized fuzzy rough set based feature evaluation selection
........................\.............................................................\certainty_s_gs.m
........................\.............................................................\certainty_theta_gs.m
........................\.............................................................\dependency_s_gs.m
........................\.............................................................\dependency_theta_gs.m
........................\.............................................................\FS_GKFS.m
........................\KNN classifier
........................\..............\KNN.m
........................\neighborhood classifier
........................\.......................\neighborhood classifier
........................\.......................\.......................\KNN.m
........................\.......................\.......................\NEC.m
........................\neighborhood mutual information based feature evaluation and selection
........................\......................................................................\FS_FW_NE.m
........................\......................................................................\NMI.m
........................\Neighborhood rough set based feature evaluation and reduction
........................\.............................................................\clsf_dpd.m
........................\.............................................................\clsf_dpd_fast.m
........................\.............................................................\clsf_dpd_fast2.m
........................\.............................................................\clsf_dpd_fast_3.m
........................\.............................................................\NRS_FW_FS.m
........................\Ranking heterogeneous features with mRMR and mutual information
............