CatBoost

CatBoost (Yandex) is arguably the easiest boosting library to use because it handles Categorical Features automatically and perfectly without tuning.

When to Use

• Tabular Data with Categorical Features: Automatic target encoding and categorical combination without manual one-hot encoding.
• Low-Latency Inference: Fast model scoring on CPU and GPU with minimal memory overhead.
• Ranking & Classification Tasks: E-commerce recommendation, fraud detection, and click-through-rate (CTR) prediction.
• Robustness Against Overfitting: Symmetric (oblivious) decision trees providing stable predictions on small-to-medium datasets.

Quick Start

from catboost import CatBoostClassifier, Pool
from sklearn.model_selection import train_test_split
import pandas as pd