def refine(dataset, n_fold = 4):
folds = divide(dataset, n_fold)
filtered_set = []
matching_scheme = exactMatch
voting_scheme = consensusVote
for i in range(n_fold):
# i-th fold is the target of refining
target_set = folds[i]
models = []
for j in range(n_fold):
if j == i:
continue
m = getModelFromPreprocessed(folds[j])
models.append(m)
# test
hits = []
for user_id, label in target_set:
context = loadPreprocessedContext(user_id)
if context is None:
continue
for m in models:
l = m.predict(context)
matched = matching_scheme(l, label)
hits.append(matched)
if voting_scheme(hits):
filtered_set.append((user_id, label))
print "Finished %d-th fold" % i
print " Outputted %d instances in %d-th fold" % (len(filtered_set), i)
return filtered_set
def getModelFromPreprocessed(dataset, meta = 0):
'''
Train a maxent classifier with Twitter data
'''
m = cmaxent.MaxentModel()
m.begin_add_event()
# add event reading the file one by one
l_count = 0 # line count
for user_id, target in dataset:
context = loadPreprocessedContext(user_id, meta = meta)
if context is None:
continue
weight = 1
m.add_event(context, target, weight)
m.end_add_event(PRUNE_COUNT)
m.train(LBFGS_ITERATION, 'lbfgs', PRIOR_WEIGHT, TOLERANCE)
return m
