[Feature Request]: Add Extreme Gradient Boosting in Machine Learning

[pavitraag]

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Feature Description

Extreme Gradient Boosting (XGBoost) is a powerful machine learning algorithm that uses gradient boosting frameworks to achieve high predictive accuracy. It builds an ensemble of decision trees sequentially, where each new tree corrects the errors of the previous ones, optimizing for a specified loss function.

Use Case

Incorporating XGBoost would enhance the project's performance in predictive analytics tasks, such as customer churn prediction or credit risk assessment. Its ability to handle large datasets and deliver high accuracy would provide valuable insights and more reliable predictions, improving overall project outcomes.

Benefits

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Priority

High

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[github-actions[bot]]

Hi @pavitraag! Thanks for opening this issue. We appreciate your contribution to this open-source project. Your input is valuable and we aim to respond or assign your issue as soon as possible. Thanks again!

[github-actions[bot]]

Hello @pavitraag! Your issue #3560 has been closed. Thank you for your contribution!