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.