search for: csadaexp

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2010 Feb 03
0
mboost: how to implement cost-sensitive boosting family
...some families I wrote ngradient <- function (y, f, w = 1) { y * ifelse(y==1,10,1) * exp(-y * f * ifelse(y==1,10,1)) } loss <- function (y, f) { exp(-y * f * ifelse(y==1,10,1)) } offset <- function (y, w) { p <- weighted.mean(y > 0, w) 1/(10+1) * log(10*p/1*(1 - p)) } CSAdaExp <- Family(ngradient = ngradient, loss = loss, offset = offset); model.blackboost <- blackboost(tr[,1:DIM], tr.y, family=CSAdaExp, weights=tr.w, control=boost_control(mstop=100, nu=0.1), tree_controls=ctree_control(teststat = "max",testtype = "Teststatistic",mincriterion =...