{"push_id":889767631,"size":1,"distinct_size":1,"ref":"refs/heads/master","head":"9150fb3c51ae75332b92286f429051c9a1f61af8","before":"667b5c70a3b2c67168cbc91f0e8df21d0ec2e124","commits":[{"sha":"9150fb3c51ae75332b92286f429051c9a1f61af8","author":{"email":"6e52ff254db0b0f0de207442c11fca5e572e007c@seas.upenn.edu","name":"Shreya Sriram"},"message":"Create libsvmcrossval_ova\n\nhttp://stackoverflow.com/questions/14024740/10-fold-cross-validation-in-one-against-all-svm-using-libsvm\r\n\r\nSAMPLE USAGE:\r\n%# load dataset\r\nS = load('fisheriris');\r\ndata = zscore(S.meas);\r\nlabels = grp2idx(S.species);\r\n\r\n%# cross-validate using one-vs-all approach\r\nopts = '-s 0 -t 2 -c 1 -g 0.25';    %# libsvm training options\r\nnfold = 10;\r\nacc = libsvmcrossval_ova(labels, data, opts, nfold);\r\nfprintf('Cross Validation Accuracy = %.4f%%\\n', 100*mean(acc));\r\n\r\n%# compute final model over the entire dataset\r\nmdl = libsvmtrain_ova(labels, data, opts);","distinct":true,"url":"https://api.github.com/repos/ShreyaSriram/CIS-562-Assignment-10/commits/9150fb3c51ae75332b92286f429051c9a1f61af8"}]}