How to generate predicted probabilities using gbm

gbm

#1

Hello,

I am using gbm for one of the classification problems and my code to predict the responses is:

pred.gbm <- predict(fit.gbm, newdata=test.rose[,1:17],
                    n.trees=best.iter, type="response")
pred.label <- 1*(pred.gbm > 0.484) #1: > 0.484; 0: otherwise

The last line is something i wish to implement but how do I find out the cutoff value,like from a specificity vs sensitivity curve?
Also

head(pred.gbm)
[1] 1.965139 1.123409 1.277245 1.001579 1.624551 1.834146

I want the predicted probabilities rather than these values.Can the reason be that I am using distribution = "laplace" and not “bernoulli”??
Can someone please help me with these??