# How to choose the 1st threshold/classifier/ weak learner in Adaboost?

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

1. Choose the classifier with the lowest error
2. $e(t)<0.5$ otherwise stop;

But if condition 1 is satisfied, doesn't it imply that condition 2 will also be satisfied automatically?