Question: Suppose you use a boosted decision tree model in a regression setting with tree depth d = 1, also known as a boosted decision stump.

Suppose you use a boosted decision tree model in a regression setting with tree depth d = 1, also known as a boosted decision stump. This results in a model that is additive in its features. Is this equivalent to linear regression? Explain your answer.

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