radiant.model (version 1.6.7)

predict.rforest: Predict method for the rforest function

Description

Predict method for the rforest function

Usage

# S3 method for rforest
predict(
  object,
  pred_data = NULL,
  pred_cmd = "",
  pred_names = "",
  OOB = NULL,
  dec = 3,
  envir = parent.frame(),
  ...
)

Arguments

object

Return value from rforest

pred_data

Provide the dataframe to generate predictions (e.g., diamonds). The dataset must contain all columns used in the estimation

pred_cmd

Generate predictions using a command. For example, `pclass = levels(pclass)` would produce predictions for the different levels of factor `pclass`. To add another variable, create a vector of prediction strings, (e.g., c('pclass = levels(pclass)', 'age = seq(0,100,20)')

pred_names

Names for the predictions to be stored. If one name is provided, only the first column of predictions is stored. If empty, the levels in the response variable of the rforest model will be used

OOB

Use Out-Of-Bag predictions (TRUE or FALSE). Relevant when evaluating predictions for the training sample. If set to NULL, datasets will be compared to determine if OOB predictions should be used

dec

Number of decimals to show

envir

Environment to extract data from

...

further arguments passed to or from other methods

Details

See https://radiant-rstats.github.io/docs/model/rforest.html for an example in Radiant

See Also

rforest to generate the result

summary.rforest to summarize results

Examples

result <- rforest(titanic, "survived", c("pclass", "sex"), lev = "Yes")
predict(result, pred_cmd = "pclass = levels(pclass)")
result <- rforest(diamonds, "price", "carat:color", type = "regression")
predict(result, pred_cmd = "carat = 1:3")
predict(result, pred_data = diamonds) %>% head()