xgboost ☆
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Description:
Scalable, Portable and Distributed Gradient Boosting Library
Type: Formula  |  Tracked Since: Dec 28, 2025
Links: Homepage  |  @xgboost  |  formulae.brew.sh
Category: Ai ml
Tags: machine-learning gradient-boosting ai data-science ml
Install: brew install xgboost
About:
XGBoost is a highly optimized, distributed gradient boosting library designed for efficiency and performance. It implements machine learning algorithms under the Gradient Boosting framework, providing a parallel tree boosting to solve many data science problems quickly and accurately.
Key Features:
  • Parallel and distributed computing for fast training
  • Handles sparse data and missing values natively
  • Built-in cross-validation and feature importance
  • Supports major languages: Python, R, Java, Scala, C++
Use Cases:
  • Winning numerous machine learning competitions on platforms like Kaggle
  • Building high-performance fraud detection and recommendation systems
  • Large-scale regression and classification tasks in enterprise environments
Alternatives:
  • LightGBM – Faster training speed and lower memory usage, but XGBoost often has slightly better accuracy
  • CatBoost – Better handling of categorical features automatically, but XGBoost has broader ecosystem support
Version History
Detected Version Rev Change Commit
Nov 26, 2024 11:24am 0 VERSION_BUMP 7989eafe
Oct 23, 2024 4:12pm 0 VERSION_BUMP fbad048b
Oct 23, 2024 3:57pm 0 VERSION_BUMP 3f3dbd60
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