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
:c
regularization 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
)
Comments
Post a Comment