I am having some difficulty understanding Adaboost.
How should the 1st threshold/classifier/weak learner be chosen?
It seems that there are two conditions which must be satisfied
- Choose the classifier with the lowest error
- $e(t)<0.5$ otherwise stop;
But if condition 1 is satisfied, doesn't it imply that condition 2 will also be satisfied automatically?