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Positive or negative in sentiment

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Reference no: EM133217770

A dataset containing 1000 product reviews has been collected. Each document is labelled in the gold standard as to whether it is positive or negative in sentiment. 10% of the labelled data is set aside as test data and the remaining 90% used to train a Naive Bayes classifier.

Describe:

How the data should be preprocessed so that a Naive Bayes Classifier could be deployed.

How a Naive Bayes Classifier is trained.

How a Naive Bayes Classifier makes predictions for documents in the test set.

Reference no: EM133217770

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