Posted On: Nov 4, 2019
Customers can now use a new version of the SageMaker XGBoost algorithm that is based on version 0.90 of the open-sourced XGBoost framework. XGBoost is a highly efficient and flexible algorithm for problems in regression, classification, and ranking.
In addition to the new features brought by the v0.9 framework, this new SageMaker release offers customers:
- Flexibility: This new release of XGBoost algorithm can be used as a built-in algorithm or as a framework. Customers migrating from the previous built-in algorithms will only need to make a small change and specify the algorithm version when they call get_image_uri to make sure they get the latest version. Customers using it as a framework will have the flexibility to specify how they want to train by providing their own training scripts.
- Scalability: this version has an improved distribution mechanism which resulted in significantly improved memory footprint, smoother experience training on larger clusters and on larger datasets.
- Extensibility: customers can extend the container image by installing new packages, adding custom scripts, or extend the container SDK that SageMaker created to build algorithms. They can also train the algorithm on their local machine.
To learn more, see documentation here.