I'm developing a naive bayes in R. I have the following data and am trying
to predict on returned (class).
dat = data.frame(home=c(0,1,1,0,0), gender=c("M","M","F","M","F"),
returned=c(0,0,1,1,0))
str(dat)
dat$home <- as.factor(dat$home)
dat$returned <- as.factor(dat$returned)
library(e1071)
m <- naiveBayes(returned ~ ., dat)
m
predict(m, dat[1:5,-3])
table(predict=predict(m, dat[1:5,-3]), true=dat[1:5,3])
predict(m, dat[1:5,-3], type = "raw")
So far, so good I think (???).
I want to know if there is any diagnostic test to determine the overall
misclassification rate
of a NB classifier, and if there is a function in R that is available to
implement it?
Thanks,
Abraham
--
*Abraham Mathew
Statistical Analyst
www.amathew.com
720-648-0108
@abmathewks*
[[alternative HTML version deleted]]
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.