def match(svmdata, modeldata):
y,x = svmutil.svm_read_problem(svmdata)
m = svmutil.svm_load_model(modeldata)
labels, accuracy, values = svmutil.svm_predict(y,x,m)
# We'll see if the labels work, and what they return, and we'll classify from there
import pdb;pdb.set_trace()
return 0
def train(model_name, svmdata):
y,x = svmutil.svm_read_problem(svmdata)
problem = svmutil.svm_problem(y,x)
param = svmutil.svm_parameter('-s 0 -t 2 -g 0.0007')
model = svmutil.svm_train(problem, param)
modelname = model_name
svmutil.svm_save_model(modelname, model)
return 0
