def main(args):
print("Loading dataset...")
train_set = utils.load_dataset(args.training_file)
print("FILE: ", args.training_file)
test_set = utils.load_dataset(args.test_file)
print("Loaded dataset")
print()
#for algorithm, name in zip([baseline, viterbi_p1, viterbi_p2, extra], ['Baseline', 'Viterbi_p1', 'Viterbi_p2', 'extra']):
for algorithm, name in zip([viterbi_p2, extra], ['Viterbi_p2', 'extra']):
print("Running {}...".format(name))
testtag_predictions = algorithm(train_set, utils.strip_tags(test_set))
baseline_acc, correct_wordtagcounter, wrong_wordtagcounter = utils.evaluate_accuracies(
test_set, testtag_predictions)
multitags_acc, unseen_acc, = utils.specialword_accuracies(
train_set, test_set, testtag_predictions)
print("Accuracy: {:.2f}%".format(baseline_acc * 100))
print("\tTop K Wrong Word-Tag Predictions: {}".format(
utils.topk_wordtagcounter(wrong_wordtagcounter, k=4)))
print("\tTop K Correct Word-Tag Predictions: {}".format(
utils.topk_wordtagcounter(correct_wordtagcounter, k=4)))
print("\tMultitags Accuracy: {:.2f}%".format(multitags_acc * 100))
print("\tUnseen words Accuracy: {:.2f}%".format(unseen_acc * 100))
print()
def main(args):
print("Loading dataset...")
train_set = utils.load_dataset(args.training_file)
test_set = utils.load_dataset(args.test_file)
print("Loaded dataset")
print()
algorithms = {
"baseline": baseline,
"viterbi_1": viterbi_1,
"viterbi_2": viterbi_2,
"viterbi_ec": viterbi_ec
}
algorithm = algorithms[args.algorithm]
print("Running {}...".format(args.algorithm))
testtag_predictions = algorithm(train_set, utils.strip_tags(test_set))
baseline_acc, correct_wordtagcounter, wrong_wordtagcounter = utils.evaluate_accuracies(
testtag_predictions, test_set)
multitags_acc, unseen_acc, = utils.specialword_accuracies(
train_set, testtag_predictions, test_set)
print("Accuracy: {:.2f}%".format(baseline_acc * 100))
print("\tMultitags Accuracy: {:.2f}%".format(multitags_acc * 100))
print("\tUnseen words Accuracy: {:.2f}%".format(unseen_acc * 100))
print("\tTop K Wrong Word-Tag Predictions: {}".format(
utils.topk_wordtagcounter(wrong_wordtagcounter, k=4)))
print("\tTop K Correct Word-Tag Predictions: {}".format(
utils.topk_wordtagcounter(correct_wordtagcounter, k=4)))
print()
