predict.crtree: Predict method for the crtree function

In radiant-rstats/radiant.model: Model Menu for Radiant: Business Analytics using R and Shiny

Predict method for the crtree function

Description

Predict method for the crtree function

Usage

## S3 method for class '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()

radiant-rstats/radiant.model documentation built on Nov. 29, 2023, 5:59 a.m.