R: Ranger prediction

predict.ranger {ranger}

R Documentation

Ranger prediction

Description

Prediction with new data and a saved forest from Ranger.

Usage

## S3 method for class 'ranger'
predict(object, data, predict.all = FALSE,
  num.trees = object$num.trees, type = "response", seed = NULL,
  num.threads = NULL, verbose = TRUE, ...)

Arguments

`object`	Ranger `ranger` object.
`data`	New test data of class `data.frame` or `gwaa.data` (GenABEL).
`predict.all`	Return individual predictions for each tree instead of aggregated predictions for all trees. Return a matrix (sample x tree) for classification and regression, a 3d array for probability estimation (sample x class x tree) and survival (sample x time x tree).
`num.trees`	Number of trees used for prediction. The first `num.trees` in the forest are used.
`type`	Type of prediction. One of 'response' or 'terminalNodes' with default 'response'. See below for details.
`seed`	Random seed used in Ranger.
`num.threads`	Number of threads. Default is number of CPUs available.
`verbose`	Verbose output on or off.
`...`	further arguments passed to or from other methods.

Details

For type = 'response' (the default), the predicted classes (classification), predicted numeric values (regression), predicted probabilities (probability estimation) or survival probabilities (survival) are returned. For type = 'terminalNodes', the IDs of the terminal node in each tree for each observation in the given dataset are returned.

For classification and predict.all = TRUE, a factor levels are returned as numerics. To retrieve the corresponding factor levels, use rf$forest$levels, if rf is the ranger object.

Value

Object of class ranger.prediction with elements

`predictions`	Predicted classes/values (only for classification and regression)
`unique.death.times`	Unique death times (only for survival).
`chf`	Estimated cumulative hazard function for each sample (only for survival).
`survival`	Estimated survival function for each sample (only for survival).
`num.trees`	Number of trees.
`num.independent.variables`	Number of independent variables.
`treetype`	Type of forest/tree. Classification, regression or survival.
`num.samples`	Number of samples.

Author(s)

Marvin N. Wright