I am trying to build a boosting model using the package gbm in R. I have the following code:
gb = gbm(aaa_target ~ ., data=myDdata, n.trees=100, verbose=TRUE)
and when I have trained the model, I can get a summary like this:
The issue I am having, is that only a single variable (out of around 30) is selected and is given 100% predictive power. I know for a fact that many of the variables carry information (although the selected one is the most significant one), and using the randomForest package gives me a model which assigns significance to many of the variables.
Does anybody have a clue to why this might be the case?