Train the Naive Bayes Classifiers in Python.

The classier uses only bag-of-word features. Assume the following parameters for each word being part of a positive or negative movie review, and the prior probabilities are 0.4 for the positive class and 0.6 for the negative class.

1) What class will Nave Bayes assign to the sentence I always like foreign lms? Show your work In Python Programming

2) Implement in Python a Nave Bayes classier with bag-of-word features and add-1 smoothing.

Note: Smoothing should be used for the context features (bag-of-word features) only. Do not use smoothing for the prior parameters.

posneg 0.090.16 always 0.07 0.06 0.290.06 foreign 0.04 0.15 films0.080.11 like posneg 0.090.16 always 0.07 0.06 0.290.06 foreign 0.04 0.15 films0.080.11 like