text: from classification import classify
  import sys
  sys.path.append('code/tools')
  from features import train_tagger
  
  #note: feats = 0: unigrams, 1: bigrams, 2: pos_tag feats, 3: description, 4: emotion feats, 5: k (num_feats)
  #note: results = 0: loss precision, 1: loss recall, 2: loss f1, 3: aggress precision, 4: aggress recall, 5: agress f1
  
  if len(sys.argv)> 1 and sys.argv[1] == 'BCS_aggress':
  	train_file = 'data/classification/_train/train_aggress_loss.csv'
  	dev_file = 'data/classification/_test/test_aggress_loss.csv'
  	model = 'svm'
  	label = 'aggress'
  	feats = []
  	C = 
  	loss = 
  
  if len(sys.argv)> 1 and sys.argv[1] == 'BCS_loss': 
  	train_file = 'data/classification/_train/train_aggress_loss.csv'
  	dev_file = 'data/classification/_test/test_aggress_loss.csv'
  	model = 'svm'
  	label = 'loss'
  	feats = []
  	C = 
  	loss = 
  
  if len(sys.argv)> 1 and sys.argv[1] == 'TCF_aggress': 
  	train_file = 'data/_train/train_full.csv'
  	dev_file = 'data/_test/test_full.csv'
  	model = 'svm'
  	label = 'aggress'
  	feats = []
  	C = 
  	loss = 
  
  if len(sys.argv)> 1 and sys.argv[1] == 'TCF_aggress_loss': 
  	train_file = 'data/_train/train_full.csv'
  	dev_file = 'data/_test/test_full.csv'
  	model = 'svm'
  	label = 'loss_aggress'
  	feats = []
  	C = 
  	loss = 
  
  if len(sys.argv)> 1 and sys.argv[1] == 'TCF_loss': 
  	train_file = 'data/_train/train_full.csv'
  	dev_file = 'data/_test/test_full.csv'
  	model = 'svm'
  	label = 'loss'
  	feats = []
  	C = 
  	loss = 
  
  pos_tagger = None
  if feats[2] == 'u' or feats[2] == 'b':
  	pos_tagger = train_tagger()
  
  results = classify(train_file, dev_file, model, label, feats=feats, pos_tagger=pos_tagger, C=C, svm_loss=loss)
  
  #output results
  print
  print 'Results'
  print 
  print 'sought precision: '+str(results[0])
  print 'sought recall: '+str(results[1])
  print 'sought f-score: '+str(results[2])
  print
  print 'nsought precision: '+str(results[3])
  print 'nsought recall: '+str(results[4])
  print 'nsought f-score: '+str(results[5])