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