# mobforest.output-class

From mobForest v1.3.1
by Kasey Jones

##### Class `"mobforest.output"`

of mobforest model

Random Forest output for model based recursive partitioning

- Keywords
- classes

##### Usage

```
# S4 method for mobforest.output
show(object)
```

##### Arguments

##### Objects from the Class

Objects can be created by
`mobforest.output`

.

##### See Also

##### Examples

```
# NOT RUN {
# }
# 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)
# }
# NOT RUN {
# }
```

*Documentation reproduced from package mobForest, version 1.3.1, License: GPL (>= 2)*

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