I've calculated an adaboost algorithm for 20 iterations with a decision tree as my weak learner. I want to make a graph that plots the training error and the testing error. I have the training error, but how do I calculate test error? If I calculated a weighted training error, must the test error also be weighted. If so, how do I determine the weights?
For test error you should not use weighting unless some data points are more important than others, which is another story with respect to weighting in Adaboost. In Adaboost different weights are used in different iterations to lean the tree towards the part of the data that the model as built up to this point performs poorly.