I am trying to understand how Adaboost works, and many of the tutorials online involve the use of a decision tree stump. For example, http://www.cc.gatech.edu/~thad/6601-gradAI-fall2013/boosting.pdf or http://www.fromdev.com/2012/04/creating-weak-learner-with-decision.html. However, I am confused on how the plot is actually generated. Say I have the following training set:
Event 1 Event 2 Event 3 Classifier 1 -1 1 1 Classifier 2 1 -1 1 Classifier 3 1 1 -1
How should I generate a decision stump for this?