library(randomForest)
library(mlbench)

data(PimaIndiansDiabetes)

head(PimaIndiansDiabetes)
rf.obj <- randomForest(diabetes~.,data=PimaIndiansDiabetes,mtry=2)

getTree(rf.obj,k=1)
varImpPlot(rf.obj)
plot(rf.obj)
rf.obj$confusion

mean(rf.obj$predicted==PimaIndiansDiabetes$diabetes)

tabl <- table(PimaIndiansDiabetes$diabetes,rf.obj$predicted)

options(digits=3)

100*diag(tabl/rowSums(tabl))
rowSums(tabl)
100*sum(diag(tabl))/sum(tabl)

tabl2 <- rbind(cbind(tabl,rowSums(tabl)),c(colSums(tabl),sum(sum(tabl))))
rownames(tabl2) <- c(rownames(tabl),"Total")
colnames(tabl2) <- c(colnames(tabl),"Total")
"Rows = actual       columns = predicted"
tabl2