libsvm - What is cross validation rate in grid.py indicate? -
i know cross validation , grid.py does.
i know parameter g , g supposed used while training have no idea third parameter rate?
i cross-validation rate 95.32 % . signify ?? or bad ??
that cross-validation rate percentage of samples has been correctly classified during cross-validation step (with best c , g parameters found), having 95% success great result. parameters of grid.py following:
-log2c:cregularization parameter-log2g: set gamma in kernel functionexp(-gamma*|u-v|^2)-v n:n-fold cross validation-svmtrain pathname: set svm executable path , name-gnuplot pathname: set gnuplot executable path , name-out pathname: set output file path , name-png pathname: set graphic output file path , name (defaultdataset.png)
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