Description Objects from the Class Slots
A forest of decision tree classifiers to be used for ensemble prediction.
Objects can be created by calls of the form new("forest", ...)
.
n
:Number of observations in dataset used to fit this forest.
p
:Number of independent variables in dataset used to fit this forest.
min_node_obs
:Leaf of any tree in this forest will not be split unless it has more observations than this value.
max_depth
:Maximum depth of any tree in this forest
numsamps
:Number of observations randomly drawn with replacement used to fit a tree in this forest.
numvars
:Number of independent variables randomly drawn without replacement used to fit a tree in this forest.
numboots
:Number of trees in this forest.
numnodes
:Vector with the number of nodes that each tree has in this forest.
flattened.nodes
:Data frame containing information on the nodes of the trees in this forest.
model
:Model frame used to fit this forest.
x
:Design (independent variables) matrix used to fit this forest.
y
:Dependent variable vector used to fit this forest.
fmla
:Formula used to construct the model frame from the data.
depvar.restore.info
:This is a slot that the package needs internally.
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