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        NaiveBayesModel
Model for Naive Bayes classifiers. Contains two parameters: - pi: vector of logs of class priors (dimension C) - theta: matrix of logs of class conditional probabilities (CxD) >>> data = array([0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 2.0, 1.0, 1.0]).reshape(3,3) >>> model = NaiveBayes.train(sc.parallelize(data)) >>> model.predict(array([0.0, 1.0])) 0 >>> model.predict(array([1.0, 0.0])) 1
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 x.__init__(...) initializes x; see help(type(x)) for signature 
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