class NaiveBayesClassifier
 |  A program to use machine learning techniques with ngram maximum likelihood probabilistic language models as feature to build a bayesian text classifier.
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 |  Methods defined here:
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 |  __init__(self, labels, location)
 |      Constructor method to load training data, and train classifier.
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 |  calculateLikelihood(self, word, label)
 |      Method to calculate Likelihood.
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 |  calculatePrior(self)
 |      Method to calculate Prior.
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 |  classify(self, document)
 |      Method to load test data and classify using training data.
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 |  createUnigram(self)
 |      Method to create Unigram for each class/label.
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 |   getDocuments(self, location)
 |      Method to retrieve test data.
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 |  loadDocuments(self, loc, files)
 |      Method to load labeled data from the training set.
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 |  train(self)
 |      Method to train classifier by calculating Prior and Likelihood.
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 |  unigramProbability(self, word, label)
 |      Method to calculate Unigram Maximum Likelihood Probability with Laplace Add-1 Smoothing.