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.
pretty.gbm.tree(object, i.tree = 1)
a gbm.object
initially fit using gbm
the index of the tree component to extract from object
and display
pretty.gbm.tree
returns a data frame. Each row corresponds to a node in
the tree. Columns indicate
index of which variable is used to split. -1 indicates a terminal node.
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.
the index of the row corresponding to the left node.
the index of the row corresponding to the right node.
the reduction in the loss function as a result of splitting this node.
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.