mobForest (version 1.3.1)

tree.predictions: Predictions from tree model

Description

This method computes predicted outcome for each observation in the data frame using the tree model supplied as an input argument.

Usage

tree.predictions(j, df, tree)

Arguments

j

the observation

df

A data frame containing the variables in the model.

tree

An object of class mob inheriting from '>BinaryTree

Value

A vector of predicted outcome

Examples

# NOT RUN {
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)

# }