tidy_ctree {autostats} | R Documentation |
tidy ctree
Description
tidy conditional inference tree. Creates easily interpretable decision tree models that be shown with the visualize_model
function.
Statistical significance required for a split , and minimum necessary samples in a terminal leaf can be controlled to create the desired tree visual.
Usage
tidy_ctree(.data, formula, minbucket = 7L, mincriterion = 0.95, ...)
Arguments
.data |
dataframe |
formula |
formula |
minbucket |
minimum amount of samples in terminal leaves, default is 7 |
mincriterion |
(1 - alpha) value between 0 -1, default is .95. lowering this value creates more splits, but less significant |
... |
optional parameters to |
Value
a ctree object
Examples
iris %>%
tidy_formula(., Sepal.Length) -> sepal_form
iris %>%
tidy_ctree(sepal_form) %>%
visualize_model()
iris %>%
tidy_ctree(sepal_form, minbucket = 30) %>%
visualize_model(plot_type = "box")
[Package autostats version 0.4.1 Index]