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(): """