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# Machine Learning Algorithms(12) — Ensemble techniques (Boosting — Xgboost Classification)

**[Towards Dev](https://daily.dev/sources/towardsdev)** · 8 min read · 3 upvotes · 0 comments

## Summary

XgBoost is an efficient and scalable machine learning algorithm that combines weak models to produce a stronger prediction. It is widely used for classification and regression tasks, especially with large datasets. XgBoost offers high performance, scalability, customizability, and handles missing values. It has advantages such as producing high-quality results and feature importances, but it can be computationally complex, prone to overfitting, and requires careful hyperparameter tuning.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdev.com/machine-learning-algorithms-12-ensemble-techniques-boosting-xgboost-classification-885c06b221e5?source=rss----a648dc4ecb66---4>

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Tags: [#data-science](https://daily.dev/tags/data-science), [#machine-learning](https://daily.dev/tags/machine-learning), [#classification](https://daily.dev/tags/classification), [#xgboost](https://daily.dev/tags/xgboost)

[View this post on daily.dev](https://daily.dev/posts/machine-learning-algorithms-12-ensemble-techniques-boosting-xgboost-classification--lxkjeg0ug)

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