Question

explain gradient boosting algorithm in machine learning?​

Answer 1

Explanation:

Gradient boosting is a machine learning technique for regression, classification and other tasks, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees.

A Gradient Boosting Machine or GBM combines the predictions from multiple decision trees to generate the final predictions. ... So, every successive decision tree is built on the errors of the previous trees. This is how the trees in a gradient boosting machine algorithm are built sequentially.

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Answer 2

꧁༒❦ANSWER❦༒꧂

Gradient boosting is a machine learning technique for regression, classification and other tasks, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees.

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