predict.supervisedPRIM: Model Predictions

In supervisedPRIM: Supervised Classification Learning and Prediction using Patient Rule Induction Method (PRIM)

Description

Perform prediction on a trained supervisedPRIM model. Output to either predicted class or positive class probability is supported.

Usage

## S3 method for class 'supervisedPRIM'
predict(object, newdata, classProb = FALSE, ...)

Arguments

object	A trained model of class supervisedPRIM returned by supervisedPRIM
newdata	The new data on which to create predictions
classProb	Should the function return the estimated class
...	additional arguments (ignored) probabilities instead of the predicted class?

Author(s)

David Shaub

Examples

# Train a model to determine if a flower is setosa
data(iris)
yData <- factor(ifelse(iris$Species == "setosa", "setosa", "other"), levels = c("setosa", "other"))
xData <- iris
xData$Species <- NULL
primModel <- supervisedPRIM(x = xData, y = yData)
# Predict on the original dataset
predictions <- predict(primModel, newdata = xData)

Example output

Loading required package: prim
Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
4: no DISPLAY variable so Tk is not available 

supervisedPRIM documentation built on May 2, 2019, 10:15 a.m.