# NOT RUN {
# Simulation model, classification rule following Hand et al. (2001)
theta90 <- varset(N = 1000, sigma = 0.1, theta = 90, threshold = 0)
dataset <- as.data.frame(cbind(theta90$explanatory, theta90$intermediate))
names(dataset) <- c(colnames(theta90$explanatory),
colnames(theta90$intermediate))
classify <- function(Y, threshold = 0) {
Y <- Y[,c("y1", "y2")]
z <- (Y > threshold)
resp <- as.factor(ifelse((z[,1] + z[,2]) > 1, 1, 0))
return(resp)
}
formula <- response~y1+y2~x1+x2
fit <- inclass(formula, data = dataset, pFUN = list(list(model = lm)),
cFUN = classify)
predict(object = fit, newdata = dataset)
data("Smoking", package = "ipred")
# explanatory variables are: TarY, NicY, COY, Sex, Age
# intermediate variables are: TVPS, BPNL, COHB
# reponse is defined by:
classify <- function(data){
data <- data[,c("TVPS", "BPNL", "COHB")]
res <- t(t(data) > c(4438, 232.5, 58))
res <- as.factor(ifelse(apply(res, 1, sum) > 2, 1, 0))
res
}
response <- classify(Smoking[ ,c("TVPS", "BPNL", "COHB")])
smoking <- cbind(Smoking, response)
formula <- response~TVPS+BPNL+COHB~TarY+NicY+COY+Sex+Age
fit <- inclass(formula, data = smoking,
pFUN = list(list(model = lm)), cFUN = classify)
predict(object = fit, newdata = smoking)
# }
# NOT RUN {
data("GlaucomaMVF", package = "ipred")
library("rpart")
glaucoma <- GlaucomaMVF[,(names(GlaucomaMVF) != "tension")]
# explanatory variables are derived by laser scanning image and intra occular pressure
# intermediate variables are: clv, cs, lora
# response is defined by
classify <- function (data) {
attach(data)
res <- ifelse((!is.na(clv) & !is.na(lora) & clv >= 5.1 & lora >=
49.23372) | (!is.na(clv) & !is.na(lora) & !is.na(cs) &
clv < 5.1 & lora >= 58.55409 & cs < 1.405) | (is.na(clv) &
!is.na(lora) & !is.na(cs) & lora >= 58.55409 & cs < 1.405) |
(!is.na(clv) & is.na(lora) & cs < 1.405), 0, 1)
detach(data)
factor (res, labels = c("glaucoma", "normal"))
}
fit <- inclass(Class~clv+lora+cs~., data = glaucoma,
pFUN = list(list(model = rpart)), cFUN = classify)
data("GlaucomaM", package = "TH.data")
predict(object = fit, newdata = GlaucomaM)
# }
Run the code above in your browser using DataCamp Workspace