File size: 2,369 Bytes
4021124 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | ############
CatBoost
############
`CatBoost <https://catboost.ai/>`__ 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:
* The implementation of ordered boosting, a permutation-driven alternative to the classic algorithm
* 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.
The following table outlines a variety of sample notebooks that address different use cases of Amazon SageMaker CatBoost algorithm.
.. list-table::
:widths: 25 25
:header-rows: 1
* - Notebook Title
- Description
* - `Tabular classification with Amazon SageMaker LightGBM and CatBoost algorithm <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/lightgbm_catboost_tabular/Amazon_Tabular_Classification_LightGBM_CatBoost.ipynb>`__
- 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 <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/lightgbm_catboost_tabular/Amazon_Tabular_Regression_LightGBM_CatBoost.ipynb>`__
- 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
`Use Amazon SageMaker Notebook Instances <https://docs.aws.amazon.com/sagemaker/latest/dg/nbi.html>`__. 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.
For detailed documentation, please refer to the `Sagemaker CatBoost Algorithm <https://docs.aws.amazon.com/sagemaker/latest/dg/catboost.html>`__.
|