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General Naive Bayes learner.
Naive Bayes is a supervised classification algorithm that uses Bayes rule to compute the fit between a new observation and some previously observed data. The observations are discrete feature vectors, with the Bayes assumption that the features are independent. Although this is hardly ever true, the classifier works well enough in practice.


NaiveBayes Hold information for a NaiveBayes classifier. 











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Calculate the logarithmic conditional probability for each class.
A dictionary is returned where the key is the class and the value is the log probability of the class. 
Train a NaiveBayes classifier on a training set.

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