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agrario
2009 Jun 17
1
gbm for cost-sensitive binary classification?
...n advise me how to implement cost-sensitive classification with gbm.
model.gbm <- gbm.fit(tr[,1:DIM],tr.y,offset = NULL,misc = NULL,distribution = "bernoulli",w = tr.w,var.monotone = NULL,n.trees = NTREE,interaction.depth = TREEDEPTH,n.minobsinnode = 10,shrinkage = 0.05,bag.fraction = BAGRATIO,train.fraction = 1.0,keep.data = TRUE,verbose = TRUE,var.names = NULL,response.name = NULL);
or
model.gbm <- gbm(tr.y ~ .,distribution = "bernoulli",data=data.frame(cbind(tr[,1:DIM],tr.y)),weights = tr.w,var.monotone=NULL,n.trees=NTREE,interaction.depth = TREEDEPTH,n.minobsinnode =...