CVOC-package: CVOC

In SchroederFabian/CVOC: Classification under varying operating conditions

Description

The package contains two functions, ebc and etc. These are methods for univariate binary classification that allow for the consideration of operating conditions and can be used as a filter, a variable selction method.

Examples

# set parameter
oc <- c(1,3,0.5)
mu <- seq(0.05,2,0.1)
sigma <- 2^seq(-3,3,0.15)
n0 <- 70
n1 <- 45
p <- 1000	

# generate data
class <- factor(c(rep(0, n0), rep(1, n1)), labels=c("neg", "pos"))
data <- matrix(ncol=length(mu)*length(sigma)+p, nrow=n0+n1)
for (i in 1:length(mu)) {
    for (j in 1:length(sigma)) {
        data[,(i-1)*length(sigma) + j] <- c(rnorm(n0, 0, 1/sigma[j]), 
                                            rnorm(n1, mu[i], sigma[j]))
    }
}

sf <- length(mu)*length(sigma)
for (j in 1:p) {
    data[,sf+j] <- rnorm(n0+n1, 0, 2)
}

# apply etc and ebc
res.etc <- etc(class, data, oc, positive="pos", p.val=TRUE)
res.ebc <- ebc(class, data, oc, positive="pos", robust=FALSE)

SchroederFabian/CVOC documentation built on May 9, 2019, 1:18 p.m.