gbm stores the collection of trees used to construct the model in a
compact matrix structure. This function extracts the information from a single
tree and displays it in a slightly more readable form. This function is mostly
for debugging purposes and to satisfy some users' curiosity.
Usage
pretty.gbm.tree(object, i.tree = 1)
Arguments
object
a gbm.object initially fit using gbm
i.tree
the index of the tree component to extract from object
and display
Value
pretty.gbm.tree returns a data frame. Each row corresponds to a node in
the tree. Columns indicate
SplitVar
index of which variable is used to split. -1 indicates a
terminal node.
SplitCodePred
if the split variable is continuous then this component
is the split point. If the split variable is categorical then this component
contains the index of object$c.split that describes the categorical
split. If the node is a terminal node then this is the prediction.
LeftNode
the index of the row corresponding to the left node.
RightNode
the index of the row corresponding to the right node.
ErrorReduction
the reduction in the loss function as a result of
splitting this node.
Weight
the total weight of observations in the node. If weights are all
equal to 1 then this is the number of observations in the node.