Is there any tool / R package available to calculate accuracy and precision of confusion matrix in R ?
yes, you can calculate Accuracy and precision in R with confusion matrix. It uses Caret package.
Here is the example :
lvs <- c("normal", "abnormal")
truth <- factor(rep(lvs, times = c(86, 258)),
levels = rev(lvs))
pred <- factor(
c(
rep(lvs, times = c(54, 32)),
rep(lvs, times = c(27, 231))),
levels = rev(lvs))
xtab <- table(pred, truth)
# load Caret package for computing Confusion matrix
library(caret)
confusionMatrix(xtab)
And Confusion Matrix for xtab would be like this :
Confusion Matrix and Statistics
truth
pred abnormal normal
abnormal 231 32
normal 27 54
Accuracy : 0.8285
95% CI : (0.7844, 0.8668)
No Information Rate : 0.75
P-Value [Acc > NIR] : 0.0003097
Kappa : 0.5336
Mcnemar's Test P-Value : 0.6025370
Sensitivity : 0.8953
Specificity : 0.6279
Pos Pred Value : 0.8783
Neg Pred Value : 0.6667
Prevalence : 0.7500
Detection Rate : 0.6715
Detection Prevalence : 0.7645
'Positive' Class : abnormal
So here is everything, that you want.