Xgboost

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Xgboost (extreme gradient boosting) is not only an algorithm. It focuses on speed, flexibility, and model performances. Its strength doesn’t only come from the algorithm, but also from all the underlying system optimization. Using xgboost in python tutorial.

Regardless of the type of prediction task at hand; Xgboost is well known to provide better solutions than other machine learning algorithms. Xgboost (or extreme gradient boost) is not a standalone algorithm in the conventional sense. It optimizes the performance of algorithms, primarily decision trees, in a gradient boosting framework while minimizing overfitting/bias through regularization. Xgboost is a tree based ensemble machine learning algorithm which is a scalable machine learning system for tree boosting. Xgboost stands for extreme gradient boosting. It uses more accurate approximations to find the best tree model. N new training data sets are formed by random sampling with replacement from the original dataset. Xgboost supports approx, hist and gpu_hist for distributed training.