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In this article https://www.analyticsvidhya.com/blog/2015/11/quick-introduction-boosting-algorithms-machine-learning/
The author indicates you combine 3 weak models into a final one using gradient boosting, but gave no detail how to combine them. Could someone explain how that's done?
The author explicitly state the three algorithms which combine weak learners to a more powerfull boosted model; AdaBoost, GradientBoosting and XGBoost with the python codes relevant to each boosting. XGboost is in his next article.
Apparently, the result is weighted average of the weak learners, where the weight is the same as the learning rate.
