Naive bayes

You can use the Naive Bayes algorithm to classify your data when features can be assumed independent. The algorithm uses independent features to calculate the probability of a specific class. For example, you might want to predict the probability that an email is spam. In that case, you would use a corpus of words associated with spam to calculate the probability the email's content is spam.

You can use the following functions to build a Naive Bayes model, view the model, and use the model to make predictions on a set of test data:

• NAIVE_BAYES
• PREDICT_NAIVE_BAYES
• PREDICT_NAIVE_BAYES_CLASSES
• GET_MODEL_SUMMARY

For a complete example of how to use the Naive Bayes algorithm in Vertica, see Classifying data using naive bayes.