I am getting very poor values with a certain data set I have. I tried to use the -v option of svm-train but later realized that this does not produce any model file for prediction.
So what is the next step after running the train with -v 10. I get some output like below but do not know how to use this for any next step (of training or prediction). I have done a fair bit of reading (in SO, the guide.pd on the libsvm site) but still have a long way to go to piece the whole thing together. The ultimate goal is to improve the accuracy of the dataset I have, nothing I have done so have has helped me go beyond a 50% accuracy.
optimization finished, #iter = 267 nu = 0.641509 obj = -67.948758, rho = 0.929905 nSV = 79, nBSV = 58
. . .
optimization finished, #iter = 236 nu = 0.864000 obj = -107.939566, rho = 0.949724 nSV = 121, nBSV = 99 Total nSV = 158 Cross Validation Accuracy = 44.8864%