CatBoost
Installation
Overview
Python package installation
CatBoost for Apache Spark installation
R package installation
Command-line version binary
Build from source
Key Features
Training parameters
Python package
CatBoost for Apache Spark
R package
Command-line version
Applying models
Objectives and metrics
Model analysis
Data format description
Parameter tuning
Speeding up the training
Data visualization
Algorithm details
FAQ
Educational materials
Development and contributions
Contacts
CatBoost
CatBoost is a machine learning algorithm that uses gradient boosting on decision trees. It is available as an open source library.
Training
Training
Training on GPU
Python train function
Cross-validation
Overfitting detector
Pre-trained data
Categorical features
Text features
Embeddings features
Applying models
Regular prediction
С and C++
Java
Node.js
Rust
Calculate metrics
Staged prediction
Applying the model in ClickHouse
Model analysis
Feature importances
Object importances
Metrics
Implemented metrics
User-defined metrics
Metrics
Recovery
Visualization tools
Jupyter Notebook
TensorBoard
Exporting models
CoreML
Python or C++
JSON
ONNX
PMML
Educational materials
Tutorials
Reference papers
Videos
