supervisedPRIM (version 2.0.0)

supervisedPRIM: Fit PRIM model to a labeled dataset

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 = "

...

additional arguments to pass to prim.box

Value

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

Details

Fit

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)