文件名称:LGMMC_v2
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- 上传时间:2012-11-16
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文件大小:246.71kb
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LGMMC是一个最大间隔聚类包。该计划包括了该算法的MATLAB代码的LG - MMC卡
-LGMMC is a package for maximum margin based clustering. The package includes the MATLAB code of the algorithm LG-MMC.
-LGMMC is a package for maximum margin based clustering. The package includes the MATLAB code of the algorithm LG-MMC.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
lgmmc(small data)/echocardiogram.mat
lgmmc(small data)/experiments.m
lgmmc(small data)/LG_MMC_v0.1/costsvmclass_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/gaussian_kernel.m
lgmmc(small data)/LG_MMC_v0.1/gradsvmclass_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/LGMMC_train.m
lgmmc(small data)/LG_MMC_v0.1/Max_Violated_y.m
lgmmc(small data)/LG_MMC_v0.1/mklsvmupdate_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/mklsvm_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/normalization.m
lgmmc(small data)/LG_MMC_v0.1/sumKbeta_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/svmclass_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1
lgmmc(small data)/Readme.htm
lgmmc(small data)
lgmmc(large scale data)/adult-8a.mat
lgmmc(large scale data)/experiments.m
lgmmc(large scale data)/LG-MMC C++/blas/blas.h
lgmmc(large scale data)/LG-MMC C++/blas/blasp.h
lgmmc(large scale data)/LG-MMC C++/blas/daxpy.c
lgmmc(large scale data)/LG-MMC C++/blas/daxpy.mexw64.pdb
lgmmc(large scale data)/LG-MMC C++/blas/daxpy.obj
lgmmc(large scale data)/LG-MMC C++/blas/ddot.c
lgmmc(large scale data)/LG-MMC C++/blas/ddot.obj
lgmmc(large scale data)/LG-MMC C++/blas/dnrm2.c
lgmmc(large scale data)/LG-MMC C++/blas/dnrm2.obj
lgmmc(large scale data)/LG-MMC C++/blas/dscal.c
lgmmc(large scale data)/LG-MMC C++/blas/dscal.obj
lgmmc(large scale data)/LG-MMC C++/blas/Makefile
lgmmc(large scale data)/LG-MMC C++/blas
lgmmc(large scale data)/LG-MMC C++/linear.cpp
lgmmc(large scale data)/LG-MMC C++/linear.cpp.bak
lgmmc(large scale data)/LG-MMC C++/linear.h
lgmmc(large scale data)/LG-MMC C++/linear.h.bak
lgmmc(large scale data)/LG-MMC C++/matlab/linear_model_matlab.c
lgmmc(large scale data)/LG-MMC C++/matlab/linear_model_matlab.c.bak
lgmmc(large scale data)/LG-MMC C++/matlab/linear_model_matlab.h
lgmmc(large scale data)/LG-MMC C++/matlab/make.m
lgmmc(large scale data)/LG-MMC C++/matlab/predict.c
lgmmc(large scale data)/LG-MMC C++/matlab/predict.mexw32
lgmmc(large scale data)/LG-MMC C++/matlab/read_sparse.c
lgmmc(large scale data)/LG-MMC C++/matlab/read_sparse.mexw32
lgmmc(large scale data)/LG-MMC C++/matlab/train.c
lgmmc(large scale data)/LG-MMC C++/matlab/train.c.bak
lgmmc(large scale data)/LG-MMC C++/matlab/train.mexw32
lgmmc(large scale data)/LG-MMC C++/matlab
lgmmc(large scale data)/LG-MMC C++/predict.c
lgmmc(large scale data)/LG-MMC C++/train.c
lgmmc(large scale data)/LG-MMC C++/tron.cpp
lgmmc(large scale data)/LG-MMC C++/tron.h
lgmmc(large scale data)/LG-MMC C++
lgmmc(large scale data)/LGMMC_large_scale_v0.1/lgmmc.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/LGMMC_prediction_large_scale.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/LGMMC_train_large_scale.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/Max_Violated_y.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/normalization.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1
lgmmc(large scale data)/Readme.htm
lgmmc(large scale data)
lgmmc(small data)/experiments.m
lgmmc(small data)/LG_MMC_v0.1/costsvmclass_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/gaussian_kernel.m
lgmmc(small data)/LG_MMC_v0.1/gradsvmclass_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/LGMMC_train.m
lgmmc(small data)/LG_MMC_v0.1/Max_Violated_y.m
lgmmc(small data)/LG_MMC_v0.1/mklsvmupdate_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/mklsvm_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/normalization.m
lgmmc(small data)/LG_MMC_v0.1/sumKbeta_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1/svmclass_lgmmc.m
lgmmc(small data)/LG_MMC_v0.1
lgmmc(small data)/Readme.htm
lgmmc(small data)
lgmmc(large scale data)/adult-8a.mat
lgmmc(large scale data)/experiments.m
lgmmc(large scale data)/LG-MMC C++/blas/blas.h
lgmmc(large scale data)/LG-MMC C++/blas/blasp.h
lgmmc(large scale data)/LG-MMC C++/blas/daxpy.c
lgmmc(large scale data)/LG-MMC C++/blas/daxpy.mexw64.pdb
lgmmc(large scale data)/LG-MMC C++/blas/daxpy.obj
lgmmc(large scale data)/LG-MMC C++/blas/ddot.c
lgmmc(large scale data)/LG-MMC C++/blas/ddot.obj
lgmmc(large scale data)/LG-MMC C++/blas/dnrm2.c
lgmmc(large scale data)/LG-MMC C++/blas/dnrm2.obj
lgmmc(large scale data)/LG-MMC C++/blas/dscal.c
lgmmc(large scale data)/LG-MMC C++/blas/dscal.obj
lgmmc(large scale data)/LG-MMC C++/blas/Makefile
lgmmc(large scale data)/LG-MMC C++/blas
lgmmc(large scale data)/LG-MMC C++/linear.cpp
lgmmc(large scale data)/LG-MMC C++/linear.cpp.bak
lgmmc(large scale data)/LG-MMC C++/linear.h
lgmmc(large scale data)/LG-MMC C++/linear.h.bak
lgmmc(large scale data)/LG-MMC C++/matlab/linear_model_matlab.c
lgmmc(large scale data)/LG-MMC C++/matlab/linear_model_matlab.c.bak
lgmmc(large scale data)/LG-MMC C++/matlab/linear_model_matlab.h
lgmmc(large scale data)/LG-MMC C++/matlab/make.m
lgmmc(large scale data)/LG-MMC C++/matlab/predict.c
lgmmc(large scale data)/LG-MMC C++/matlab/predict.mexw32
lgmmc(large scale data)/LG-MMC C++/matlab/read_sparse.c
lgmmc(large scale data)/LG-MMC C++/matlab/read_sparse.mexw32
lgmmc(large scale data)/LG-MMC C++/matlab/train.c
lgmmc(large scale data)/LG-MMC C++/matlab/train.c.bak
lgmmc(large scale data)/LG-MMC C++/matlab/train.mexw32
lgmmc(large scale data)/LG-MMC C++/matlab
lgmmc(large scale data)/LG-MMC C++/predict.c
lgmmc(large scale data)/LG-MMC C++/train.c
lgmmc(large scale data)/LG-MMC C++/tron.cpp
lgmmc(large scale data)/LG-MMC C++/tron.h
lgmmc(large scale data)/LG-MMC C++
lgmmc(large scale data)/LGMMC_large_scale_v0.1/lgmmc.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/LGMMC_prediction_large_scale.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/LGMMC_train_large_scale.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/Max_Violated_y.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1/normalization.m
lgmmc(large scale data)/LGMMC_large_scale_v0.1
lgmmc(large scale data)/Readme.htm
lgmmc(large scale data)
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