k近邻法分类和ROC曲线
是不是有几个类就要画几个ROC曲线啊？
data(iris)
library(kknn)
library(caret)
index <- sample(1:nrow(iris), size=round(nrow(iris)/3), replace=FALSE)
trainSet <- iris[-index, ]
testSet <- iris[index, ]
iris.kknn <- kknn(Species~., trainSet, testSet, distance=2, kernel="triangular")
summary(iris.kknn)
Fit.kknn <- fitted(iris.kknn)
table(testSet$Species, Fit.kknn)
confusionMatrix(testSet$Species, Fit.kknn)
library(ROCR)
library(gplots)
data(iris)
score <- list()
label <- list()
pred <- list()
pref <- list()
AUC <- list()
attributes(iris.kknn)
for(i in 1:length(levels(iris$Species))){
score[[i]] <- iris.kknn$prob[,i]
}
colour <- c("red", "green", "blue")
for(i in 1:length(score)){
label[[i]] <- c(0)
label[[i]] <- c(label[[i]], testSet$Species==levels(iris$Species)[i])
label[[i]] <- label[[i]][-1]
sort_index <- order(score[[i]], decreasing=TRUE)
score[[i]] <- score[[i]][sort_index]
label[[i]] <- label[[i]][sort_index]
pred[[i]] <- prediction(score[[i]], label[[i]])
pref[[i]] <- performance(pred[[i]], "tpr", "fpr")
AUC[[i]] <- performance(pred[[i]], "auc")
if(i==1){
plot(pref[[i]], col=colour[i])
}
else{
plot(pref[[i]], add=TRUE, col=colour[i])
}
}