Predict the Leaf Node Assignment on an H2O Model

Obtains leaf node assignment from fitted H2O model objects.

predict_leaf_node_assignment.H2OModel(object, newdata, type = c("Path",
  "Node_ID"), ...)

h2o.predict_leaf_node_assignment(object, newdata, type = c("Path",
  "Node_ID"), ...)

Arguments

object	a fitted H2OModel object for which prediction is desired
newdata	An H2OFrame object in which to look for variables with which to predict.
type	choice of either "Path" when tree paths are to be returned (default); or "Node_ID" when the output
...	additional arguments to pass on.

Value

Returns an H2OFrame object with categorical leaf assignment identifiers for each tree in the model.

Details

For every row in the test set, return the leaf placements of the row in all the trees in the model. Placements can be represented either by paths to the leaf nodes from the tree root or by H2O's internal identifiers. The order of the rows in the results is the same as the order in which the data was loaded

See also

h2o.gbm and h2o.randomForest for model generation in h2o.

Examples

# NOT RUN {
library(h2o)
h2o.init()
prosPath <- system.file("extdata", "prostate.csv", package="h2o")
prostate.hex <- h2o.uploadFile(path = prosPath)
prostate.hex$CAPSULE <- as.factor(prostate.hex$CAPSULE)
prostate.gbm <- h2o.gbm(3:9, "CAPSULE", prostate.hex)
h2o.predict(prostate.gbm, prostate.hex)
h2o.predict_leaf_node_assignment(prostate.gbm, prostate.hex)
# }