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Exercise

Examining "raw" probabilities

The naivebayes package offers several ways to peek inside a Naive Bayes model.

Typing the name of the model object provides the a priori (overall) and conditional probabilities of each of the model's predictors. If one were so inclined, you might use these for calculating posterior (predicted) probabilities by hand.

Alternatively, R will compute the posterior probabilities for you if the type = "prob" parameter is supplied to the predict() function.

Using these methods, examine how the model's predicted 9am location probability varies from day-to-day. The model locmodel that you fit in the previous exercise is available for you to use, and the naivebayes package has been pre-loaded.

Instructions
100 XP
  • Print the locmodel object to the console to view the computed a priori and conditional probabilities.
  • Use the predict() function similarly to the previous exercise, but with type = "prob" to see the predicted probabilities for Thursday at 9am.
  • Compare these to the predicted probabilities for Saturday at 9am.
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