R语言 朴素贝叶斯分类器 naive Bayes classifier

朴素贝叶斯分类器示例

rm(list=ls())
library(kernlab)
data(spam)
data <- spam
id <- sample(1:4601,4000)
train <- data[id,]
test <- data[-id,]

library(e1071)
nb=naiveBayes(type~., data=train)

pred2 <- predict(nb, test, type = "class")  
table(pred2,test$type)

#pred2     nonspam spam
#  nonspam     201   11
#  spam        156  233

mean(pred2!=test$type)
# [1] 0.2778702

代入loss matrix中，需要在predict中的type设为raw

			              predicted
L=	observed    nonspam     0   1
			    spam        10  0

p=predict(nb, newdata=test, type = "raw")   # 直接返回近01两者的概率
pred2 <- ifelse(p[,1]*10>p[,2],"nonspam","spam")
table(pred2,test$type)

pred2     nonspam spam
  nonspam     210   11
  spam        147  233

mean(pred2!=test$type)
[1] 0.2628952