def main():
from altbayes import classify, train
train()
fscore(classify, get_paths())
def main():
from altbayes import classify, train
train()
fscore(classify, get_paths())
def test_pang_lee():
"""
Tests the Pang Lee dataset
"""
total, correct = 0, 0
for fname in os.listdir("txt_sentoken/pos"):
correct += int(classify2(open("txt_sentoken/pos/" + fname).read()) == True)
total += 1
for fname in os.listdir("txt_sentoken/neg"):
correct += int(classify2(open("txt_sentoken/neg/" + fname).read()) == False)
total += 1
print "accuracy: %f" % (correct / total)
if __name__ == '__main__':
train()
feature_selection_trials()
# test_pang_lee()
# classify_demo(open("pos_example").read())
# classify_demo(open("neg_example").read())
########NEW FILE########
__FILENAME__ = metric
"""
F-Score metrics for testing classifier, also includes functions for data extraction.
Author: Vivek Narayanan
"""
import os
def get_paths():
"""
