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 function exp(-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 (default dataset.png)

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