def main():
"""Trains all of the language models and tests them on the dev data. Change devPath if you
wish to do things like test on the training data."""
# load training data
trainPath = 'data/tagged-train.dat'
trainingCorpus = Corpus(trainPath)
# load dev data
devPath = 'data/tagged-dev.dat'
devCorpus = Corpus(devPath)
print 'Unigram Language Model: '
unigramLM = UnigramModel(trainingCorpus)
unigramSpell = SpellCorrect(unigramLM, trainingCorpus)
unigramOutcome = unigramSpell.evaluate(devCorpus)
print str(unigramOutcome)
print 'Uniform Language Model: '
uniformLM = UniformModel(trainingCorpus)
uniformSpell = SpellCorrect(uniformLM, trainingCorpus)
uniformOutcome = uniformSpell.evaluate(devCorpus)
print str(uniformOutcome)
print 'Smooth Unigram Language Model: '
smoothUnigramLM = SmoothUnigramModel(trainingCorpus)
smoothUnigramSpell = SpellCorrect(smoothUnigramLM, trainingCorpus)
smoothUnigramOutcome = smoothUnigramSpell.evaluate(devCorpus)
print str(smoothUnigramOutcome)
print 'Smooth Bigram Language Model: '
smoothBigramLM = SmoothBigramModel(trainingCorpus)
smoothBigramSpell = SpellCorrect(smoothBigramLM, trainingCorpus)
smoothBigramOutcome = smoothBigramSpell.evaluate(devCorpus)
print str(smoothBigramOutcome)
print 'Backoff Language Model: '
backoffLM = BackoffModel(trainingCorpus)
backoffSpell = SpellCorrect(backoffLM, trainingCorpus)
backoffOutcome = backoffSpell.evaluate(devCorpus)
print str(backoffOutcome)
print 'Custom Language Model: '
customLM = CustomModel(trainingCorpus)
customSpell = SpellCorrect(customLM, trainingCorpus)
customOutcome = customSpell.evaluate(devCorpus)
print str(customOutcome)
def main():
"""Trains all of the language models and tests them on the dev data. Change devPath if you
wish to do things like test on the training data."""
trainPath = 'data/tagged-train.dat'
trainingCorpus = Corpus(trainPath)
devPath = 'data/tagged-dev.dat'
devCorpus = Corpus(devPath)
print 'Unigram Language Model: '
unigramLM = UnigramModel(trainingCorpus)
unigramSpell = SpellCorrect(unigramLM, trainingCorpus)
unigramOutcome = unigramSpell.evaluate(devCorpus)
print str(unigramOutcome)
print 'Uniform Language Model: '
uniformLM = UniformModel(trainingCorpus)
uniformSpell = SpellCorrect(uniformLM, trainingCorpus)
uniformOutcome = uniformSpell.evaluate(devCorpus)
print str(uniformOutcome)
'''