sinsa110 / tutorials

CatBoost tutorials repository

Tutorials

Python tutorials

• Main CatBoost tutorial with base features demonstration:

  • Python Tutorial
    • This tutorial shows some base cases of using catboost, such as model training, cross-validation and predicting, as well as some useful features like early stopping, snapshot support, feature importances and parameters tuning.

• CatBoost model analysis tutorials:

  • Object Importance Tutorial

    • This tutorial shows how to evaluate importances of the train objects for test objects. And with using of importance scores detect noisy train objects.

  • SHAP Values Tutorial

    • This tutorial shows how to use SHAP python-package to get and visualize feature importances.

• CatBoost performance at different competitions:

  • Kaggle Paribas Tutorial

    • This tutorial shows how to get to a 9th place on paribas competition with only few lines of code and training a CatBoost model.

  • ML Boot Camp Tutorial

    • This is an actual 7th place solution by Mikhail Pershin. Solution is very simple and is based on CatBoost.

• CatBoost and TensorFlow:

  • CatBoost & TensorFlow Tutorial
    • This tutorial shows how to use CatBoost together with TensorFlow if you have text as input data.

• CatBoost and CoreML:

  • CatBoost CoreML Tutorial
    • This tutorial shows how to convert CatBoost model to CoreML format and use it on an iPhone.

R tutorials

• Main CatBoost tutorial with base features demonstration:
  • R Tutorial
    • This tutorial shows how to convert your data to CatBoost Pool, how to train a model and how to make cross validation and parameter tunning.

Command line tutorials

• Main CatBoost tutorial with base features demonstration:
  • Command Line Tutorial
    • This tutorial shows how to train and apply model with the command line tool.

Custom loss tutorial

• Adding custom per-object error function tutorial:
  • Custom Metrics Tutorial
    • This tutorial shows how to add custom per-object metrics.