Strong(er) Gradient Boosting

The idea of boosting in machine learning is based on the question posed by Michael Kearns and Leslie Valiant in 1988/89: “Can a set of weak learners create a single strong learner?”

In a seminal paper that came out a year later, “The strength of weak learnability”, Robert Schapire provided an affirmative answer to this question, describing a method “for converting a weak learning algorithm into one that achieves arbitrarily high accuracy”.

A …

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