Description Usage Arguments Value Examples
View source: R/tree.predictions.R
This method computes predicted outcome for each observation in the data frame using the tree model supplied as an input argument.
1 | tree.predictions(j, df, tree)
|
j |
the observation |
df |
A data frame containing the variables in the model. |
tree |
An object of class mob inheriting from
|
A vector of predicted outcome
1 2 3 4 5 6 7 8 9 10 | library(mlbench)
set.seed(1111)
# Random Forest analysis of model based recursive partitioning load data
data("BostonHousing", package = "mlbench")
data <- BostonHousing[1:90, c("rad", "tax", "crim", "medv", "lstat")]
fmBH <- mob.rf.tree(main_model = "medv ~ lstat",
partition_vars = c("rad", "tax", "crim"), mtry = 2,
control = mob_control(), data = data,
model = linearModel)
tree.predictions(j = 1, df = data, tree = fmBH@tree)
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