You can use a table to compare your predicted values and the response. Here is an example: http://www.cyclismo.org/tutorial/R/tables.html
On Thu, Aug 2, 2012 at 5:52 AM, Abraham Mathew <[email protected]> wrote: > 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. ______________________________________________ [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.
