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Exercise

Try a longer tune length

Recall from the video that random forest models have a primary tuning parameter of mtry, which controls how many variables are exposed to the splitting search routine at each split. For example, suppose that a tree has a total of 10 splits and mtry = 2. This means that there are 10 samples of 2 predictors each time a split is evaluated.

Use a larger tuning grid this time, but stick to the defaults provided by the train() function. Try a tuneLength of 3, rather than 1, to explore some more potential models, and plot the resulting model using the plot function.

Instructions
100 XP
  • Train a random forest model, model, using the wine dataset on the quality variable with all other variables as explanatory variables. (This will take a few seconds to run, so be patient!)
  • Use method = "ranger".
  • Change the tuneLength to 3.
  • Use 5 CV folds.
  • Print model to the console.
  • Plot the model after fitting it.