A simple Naive Bayes location model

The previous exercises showed that the probability that Brett is at work or at home at 9am is highly dependent on whether it is the weekend or a weekday.

To see this finding in action, use the where9am data frame to build a Naive Bayes model on the same data.

You can then use this model to predict the future: where does the model think that Brett will be at 9am on Thursday and at 9am on Saturday?

The data frame where9am is available in your workspace. This dataset contains information about Brett's location at 9am on different days.

This exercise is part of the course

Supervised Learning in R: Classification

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Exercise instructions

Load the naivebayes package.
Use naive_bayes() with a formula like y ~ x to build a model of location as a function of daytype.
Forecast the Thursday 9am location using predict() with the thursday9am object as the newdata argument.
Do the same for predicting the saturday9am location.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Load the naivebayes package


# Build the location prediction model
locmodel <- naive_bayes(___, data = ___)

# Predict Thursday's 9am location
predict(___, ___)

# Predict Saturdays's 9am location

Edit and Run Code