mobforest.output-class: Class '"mobforest.output"' of mobforest model

In RTIInternational/mobForest: Model Based Random Forest Analysis

Description

Random Forest output for model based recursive partitioning

Usage

## S4 method for signature 'mobforest.output'
show(object)

Arguments

object

object of class mobforest.output

Objects from the Class

Objects can be created by mobforest.output.

See Also

prediction.output, varimp.output

Examples

## Not run: 
library(mlbench)
set.seed(1111)
# Random Forest analysis of model based recursive partitioning load data
data("BostonHousing", package = "mlbench")
BostonHousing <- BostonHousing[1:90, c("rad", "tax", "crim", "medv", "lstat")]

# Recursive partitioning based on linear regression model medv ~ lstat with 3
# trees.  1 core/processor used. 
rfout <- mobforest.analysis(as.formula(medv ~ lstat), c("rad", "tax", "crim"),
    mobforest_controls = mobforest.control(ntree = 3, mtry = 2, replace = TRUE,
        alpha = 0.05, bonferroni = TRUE, minsplit = 25), data = BostonHousing,
    processors = 1, model = linearModel, seed = 1111)

## End(Not run)

RTIInternational/mobForest documentation built on Aug. 3, 2019, 8:28 a.m.