# prostate example -------------------------------------------------------------
# pg 49 ESL
library(ElemStatLearn)
data(prostate)
# gleason and pgg45 are categorical vars
prostate <- prostate[, setdiff(colnames(prostate), c("gleason", "pgg45"))]
obs <- prostate[, setdiff(colnames(prostate), c("train"))]
class_id <- "svi"
split <- prostate[, "train"]
sd_min <- 0.05
epsilon <- 0.25
quants <- seq(0.1, 0.9, 0.1)
method <- "fan"
augm <- TRUE
prostate_mqc <- mqc(prostate[, setdiff(colnames(prostate), c("train"))],
"svi", prostate[, "train"], 0.25, 0.25, augm=TRUE)
## Using qda
library(MASS)
prostate_qda <- qda(svi ~ lcavol + lweight + age + lbph + lcp + lpsa,
data=prostate[prostate$train, ])
prostate_qda_pred <- predict(prostate_qda, prostate[!prostate$train, ])
table(prostate_qda_pred$class, prostate[!prostate$train, "svi"])
train <- list(x = subset(prostate, train, c("lcavol", "lweight", "age", "lbph", "lcp", "lpsa")),
y = with(prostate, svi[train]))
test <- list(x = subset(prostate, !train, c("lcavol", "lweight", "age", "lbph", "lcp", "lpsa")),
y = with(prostate, svi[!train]))
# bone example -----------------------------------------------------------------
library(ElemStatLearn)
data(bone, package="ElemStatLearn")
data(orange4.train, package="ElemStatLearn")
data(orange4.test, package="ElemStatLearn")
data(orange10.train, package="ElemStatLearn")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.