Contents
Overview of CatBoost
Installation
Python package
R package
Command-line version
Applying models
Objectives and metrics
Model analysis
Data format description
Parameter tuning
Speeding up the training
Data visualization
FAQ
Educational materials
Development and contributions
Algorithm details
Contacts
Train a model
Cross-validation
Apply a model
Calculate metrics
Calculate feature importance
Calculate object importance
Metadata manipulation
Sum models
Usage examples
Overview of CatBoost
Installation
Python package installation
pip install
conda install
Build from source on Linux and macOS
Build from source on Windows
Build a wheel package
Additional packages for data visualization support
Test CatBoost
R package installation
Install the released version
conda install
Build from source
Install from a local copy on Linux and macOS