I recently read the below piece while I was learning about ensembles/boosting:
From what I understand:
If there are 10 variables in the X’s,at first all the variables have equal weight but in consequent stages the same dataset has variables whose weights are assigned according to how they have performed in the previous stage.
So if the variable income(say) has given a wrong classification for the response Y it is given more weight .
But I am not sure that this is the correct interpretation,so can someone please help me with this??