# learning rate in Adaboost sklearn

I can't figure out what does learning_rate stand for in sklearn implementation of Adaboost. When i see the original algorithm i don't see any "learning_rate"...

Meanwhile i can see from https://fr.wikipedia.org/wiki/AdaBoost that the training errors are weighted thanks to $$D_t(i)$$ (where $$i$$ is attached to the $$i$$th training instance in the training matrix $$X$$). Is there any relation between the sklearn "learning_rate" and this $$D_t$$ ?