CatBoost - Amazon SageMaker
Amazon EC2 instance recommendation for the CatBoost algorithmSample Notebooks

CatBoost

CatBoost is a popular and high-performance open-source implementation of the Gradient Boosting Decision Tree (GBDT) algorithm. GBDT is a supervised learning algorithm that attempts to accurately predict a target variable by combining an ensemble of estimates from a set of simpler and weaker models.

CatBoost introduces two critical algorithmic advances to GBDT:

  1. The implementation of ordered boosting, a permutation-driven alternative to the classic algorithm

  2. An innovative algorithm for processing categorical features

Both techniques were created to fight a prediction shift caused by a special kind of target leakage present in all currently existing implementations of gradient boosting algorithms. This page includes information about Amazon EC2 instance recommendations and sample notebooks for CatBoost.

Amazon EC2 instance recommendation for the CatBoost algorithm

SageMaker CatBoost currently only trains using CPUs. CatBoost is a memory-bound (as opposed to compute-bound) algorithm. So, a general-purpose compute instance (for example, M5) is a better choice than a compute-optimized instance (for example, C5). Further, we recommend that you have enough total memory in selected instances to hold the training data.

CatBoost sample notebooks

The following table outlines a variety of sample notebooks that address different use cases of Amazon SageMaker CatBoost algorithm.

Notebook Title Description

Tabular classification with Amazon SageMaker LightGBM and CatBoost algorithm

This notebook demonstrates the use of the Amazon SageMaker CatBoost algorithm to train and host a tabular classification model.

Tabular regression with Amazon SageMaker LightGBM and CatBoost algorithm

This notebook demonstrates the use of the Amazon SageMaker CatBoost algorithm to train and host a tabular regression model.

For instructions on how to create and access Jupyter notebook instances that you can use to run the example in SageMaker, see Amazon SageMaker Notebook Instances. After you have created a notebook instance and opened it, choose the SageMaker Examples tab to see a list of all of the SageMaker samples. To open a notebook, choose its Use tab and choose Create copy.