radiant.model (version 1.6.7)

predict.crtree: Predict method for the crtree function

Description

Predict method for the crtree function

Usage

# S3 method for crtree
predict(
  object,
  pred_data = NULL,
  pred_cmd = "",
  conf_lev = 0.95,
  se = FALSE,
  dec = 3,
  envir = parent.frame(),
  ...
)

Arguments

object

Return value from crtree

pred_data

Provide the dataframe to generate predictions (e.g., titanic). 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)')

conf_lev

Confidence level used to estimate confidence intervals (.95 is the default)

se

Logical that indicates if prediction standard errors should be calculated (default = FALSE)

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/crtree.html for an example in Radiant

See Also

crtree to generate the result

summary.crtree to summarize results

Examples

result <- crtree(titanic, "survived", c("pclass", "sex"), lev = "Yes")
predict(result, pred_cmd = "pclass = levels(pclass)")
result <- crtree(titanic, "survived", "pclass", lev = "Yes")
predict(result, pred_data = titanic) %>% head()