Description Usage Arguments Details Value References Examples
View source: R/mobforest.control.R
Various parameters that control the forest growing.
1 2 3 4 |
ntree |
Number of trees to be constructed in forest (default = 300). |
mtry |
Number of input variables randomly sampled as candidates at each node. |
replace |
logical. replace = TRUE (default) performs bootstrapping. replace = FALSE performs sampling without replacement. |
fraction |
Number of observations to draw without replacement (only relevant if replace = FALSE). |
alpha |
A node is considered for splitting if the p value for any partitioning variable in that node falls below alpha (default 0.05). Please see mob_control(). |
bonferroni |
logical. Should p values be Bonferroni corrected? (default TRUE). Please see mob_control(). |
minsplit |
An integer. The minimum number of observations in a node (default 20). Please see mob_control(). |
trim |
A numeric, as defined in mob_control(). |
objfun |
A function, as defined in mob_control(). |
breakties |
A logical, as defined in mob_control(). |
parm |
A numeric or vector, as defined in mob_control(). |
verbose |
A logical, as defined in mob_control(). |
This function is used to set up forest controls. The mob_control (from party 'package') object is used to set up control parameters for single tree model. For most parameters, please see: mob_control()
An object of class mobforest.control
.
Achim Zeileis, Torsten Hothorn, and Kurt Hornik (2008).
Model-Based Recursive Partitioning. Journal of Computational and
Graphical Statistics, 17(2), 492-514.
1 2 3 | # create forest controls before starting random forest analysis
mobforest_control = mobforest.control(ntree = 400, mtry = 4, replace = TRUE,
minsplit = 200)
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