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  3. Supervised Learning in R: Regression

Exercise

Visualize random forest bike model predictions

In the previous exercise, you saw that the random forest bike model did better on the August data than the quasiposson model, in terms of RMSE.

In this exercise, you will visualize the random forest model's August predictions as a function of time. The corresponding plot from the quasipoisson model that you built in a previous exercise is available for you to compare.

Recall that the quasipoisson model mostly identified the pattern of slow and busy hours in the day, but it somewhat underestimated peak demands. You would like to see how the random forest model compares.

The data frame bikesAugust (with predictions) has been made available for you. The plot quasipoisson_plot of quasipoisson model predictions as a function of time is shown.

Instructions

100 XP
  • Fill in the blanks to plot the predictions and actual counts by hour for the first 14 days of August.
    • gather the cnt and pred columns into a column called value, with a key called valuetype.
    • Plot value as a function of instant (day).

How does the random forest model compare?