supervisedPRIM: Fit PRIM model to a labeled dataset

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

Description

perform supervised classification using Patient Rule Induction Method (PRIM)

Usage

supervisedPRIM(x, y, peel.alpha = 0.05, paste.alpha = 0.01,
  mass.min = 0.05, threshold.type = 1, ...)

Arguments

x	matrix of data values
y	binary vector of 0/1 response values
peel.alpha	peeling quantile tuning parameter
paste.alpha	pasting quantile tuning parameter
mass.min	minimum mass tuning parameter
threshold.type	threshold direction indicator: 1 = ">= threshold", -1 = "<= threshold"
...	additional arguments to pass to prim.box

Details

Fit

Value

an object of class supervisedPRIM. See additional details in prim.box

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)

Example output

Loading required package: prim
Warning messages:
1: no DISPLAY variable so Tk is not available 
2: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
3: 'rgl.init' failed, running with 'rgl.useNULL = TRUE'. 

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