README.md

In ao90/PRIM: Patient Rule Induction Method (PRIM)

PRIM package

Implementation of the Patient Rule Induction Method (PRIM) as suggested by Friedman and Fisher (1999) in R.

Installation

You can install the latest version from Github

# install.packages("devtools")
library(devtools)
install_github("ao90/PRIM") 

Usage

Documentations:

For function documentations see manual (https://github.com/ao90/PRIM/blob/master/PRIM-manual.pdf).

Example:

library(PRIM)

# generating random data:
set.seed(123)
n <- 500
x1 <- runif(n = n, min = -1)
x2 <- runif(n = n, min = -1)
x3 <- runif(n = n, min = -1)
cat <- as.factor(sample(c("a","b","c", "d"), size = n, replace = TRUE))
wsk <- (1-sqrt(x1^2+x2^2)/sqrt(2))
y <- as.logical(rbinom(n = n, prob = wsk, size = 1))
dat <- cbind.data.frame(y, x1, x2, x3, cat)
#plot(dat$x1, dat$x2, col=dat$y+1, pch=16)
remove(x1, x2, x3, y, wsk, cat, n)

# run (multiple) peeling and show trajectory:
prim <- PRIM_peel_bs(formula=y ~ ., data=dat, beta_min = .01)
plot(prim) # multiple trajectory
head(prim$box) # box definitions

# apply the PRIM function to find the best boxes with a support of at least 0.1:
p <- PRIM(y~., data=dat, beta_min = 0.1, max_boxes = 3)
p

License

This package is free and open source software, licensed under GPL (>= 3).

ao90/PRIM documentation built on May 5, 2019, 8:01 p.m.