supervisedPRIM {supervisedPRIM} | R Documentation |
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 = "<= threshold" |
... |
additional arguments to pass to |
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)
[Package supervisedPRIM version 2.0.0 Index]