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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 $D_t$ ?

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