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Machine Learning

XGBoost

A highly optimised implementation of gradient-boosted decision trees.

XGBoost extends gradient boosting with regularisation, efficient tree construction, missing-value handling and parallel processing. These improvements make it fast and highly competitive for classification, regression and ranking tasks.

It became especially popular through data-science competitions and business applications involving tabular data. Strong performance still requires thoughtful feature engineering and parameter tuning.

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