old_contents: from tools.load import LoadMatrix
  lm=LoadMatrix()
  
  traindat = lm.load_numbers('../data/fm_train_real.dat')
  testdat  = lm.load_numbers('../data/fm_test_real.dat')
  label_traindat = lm.load_labels('../data/label_train_multiclass.dat')
  
  parameter_list = [[traindat,testdat,label_traindat,2.1,1,1e-5],[traindat,testdat,label_traindat,2.2,1,1e-5]]
  
  def classifier_multiclassmachine_modular (fm_train_real=traindat,fm_test_real=testdat,label_train_multiclass=label_traindat,width=2.1,C=1,epsilon=1e-5):
  	from shogun.Features import RealFeatures, Labels
  	from shogun.Classifier import LibLinear, L2R_L2LOSS_SVC, LinearMulticlassMachine, ONE_VS_REST_STRATEGY, ONE_VS_ONE_STRATEGY
  
  	feats_train = RealFeatures(fm_train_real)
  	feats_test  = RealFeatures(fm_test_real)
  
  	labels = Labels(label_train_multiclass)
  
  	classifier = LibLinear(L2R_L2LOSS_SVC)
  	classifier.set_epsilon(epsilon)
  	classifier.set_bias_enabled(True)
  	mc_classifier = LinearMulticlassMachine(ONE_VS_ONE_STRATEGY, feats_train, classifier, labels)
  
  	mc_classifier.train()
  	out = mc_classifier.apply().get_labels()
  	return out
  
  if __name__=='__main__':
  	print 'MulticlassMachine'
  	classifier_multiclassmachine_modular(*parameter_list[0])
  
new_contents: from tools.load import LoadMatrix
  lm=LoadMatrix()
  
  traindat = lm.load_numbers('../data/fm_train_real.dat')
  testdat  = lm.load_numbers('../data/fm_test_real.dat')
  label_traindat = lm.load_labels('../data/label_train_multiclass.dat')
  
  parameter_list = [[traindat,testdat,label_traindat,2.1,1,1e-5],[traindat,testdat,label_traindat,2.2,1,1e-5]]
  
  def classifier_multiclasslinearmachine_modular (fm_train_real=traindat,fm_test_real=testdat,label_train_multiclass=label_traindat,width=2.1,C=1,epsilon=1e-5):
  	from shogun.Features import RealFeatures, Labels
  	from shogun.Classifier import LibLinear, L2R_L2LOSS_SVC, LinearMulticlassMachine, ONE_VS_REST_STRATEGY, ONE_VS_ONE_STRATEGY
  
  	feats_train = RealFeatures(fm_train_real)
  	feats_test  = RealFeatures(fm_test_real)
  
  	labels = Labels(label_train_multiclass)
  
  	classifier = LibLinear(L2R_L2LOSS_SVC)
  	classifier.set_epsilon(epsilon)
  	classifier.set_bias_enabled(True)
  	mc_classifier = LinearMulticlassMachine(ONE_VS_ONE_STRATEGY, feats_train, classifier, labels)
  
  	mc_classifier.train()
  	out = mc_classifier.apply().get_labels()
  	return out
  
  if __name__=='__main__':
  	print 'MulticlassMachine'
  	classifier_multiclasslinearmachine_modular(*parameter_list[0])
  
subject: rename function to match file name