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libsvm_gridlinear

parameter selection tool for linear classification

Calling Sequence

[best_rate,best_c,best_s] = libsvm_gridlinear(label,instance)
[best_rate,best_c,best_s] = libsvm_gridlinear(label,instance,log2c)
[best_rate,best_c,best_s] = libsvm_gridlinear(label,instance,log2c,s_seq)
[best_rate,best_c,best_s] = libsvm_gridlinear(label,instance,log2c,s_seq,v)
[best_rate,best_c,best_s] = libsvm_gridlinear(label,instance,log2c,s_seq,v,option_string)

Parameters

log2c :

[begin,end,step]

s_seq :

linear kernels (0 - 7, 11 - 13), e.g. [0 1 4]

v :

fold

option_string:

additional parameters for svmtrain

best_rate :

cross validation accuracy for the best parameter combination

best_c :

best parameter c

best_s :

best linear kernel

Description

libsvm_gridlinear is a parameter selection tool for linear classification. It uses cross validation (CV) technique to estimate the accuracy of each parameter combination in the specified range and helps you to decide the best parameters for your problem.

Examples

[label,instance]=libsvmread(fullfile(libsvm_getpath(),"demos","heart_scale"));
[best_rate,best_c,best_s] = libsvm_gridlinear(label,instance)

See also

Authors

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