Classification, Part IL. Classification Tree
A
Build a classification tree that predicts the review score that a rental in your
neighborhood will have. Before you can do this, you will need to first bin the
review_scores_rating variable -- the number of bins you create is up to you
Do not use any of the other review _scores variables as inputs.
B. Determine the ideal size of your tree using cross-validation.
C. Using part.plot and your choice of graphical parameters, show your tree
model here.
D.
In a 1-2 paragraph write-up, describe your process. Talk about some of the
features that you considered using, and your reasons why. Mention anything
that you found interesting as you explored various possible models, and the
process you used to arrive at the model you finished with. Talk about the
relative sizes of each bin (using the number of records per bin) and how that
may have impacted your model.