LightGBM

LightGBM is Microsoft's gradient boosting library. It is often faster and uses less memory than XGBoost due to leaf-wise tree growth.

When to Use

• High-Speed Tabular Machine Learning: Ultra-fast gradient boosting on large tabular datasets using histogram-based algorithms.
• Massive Row-Count Datasets: Training efficiently on millions of rows with low memory consumption (GOSS and EFB).
• Ranking & Recommendation Systems: LambdaMART ranking algorithms for search engines and recommendation feeds.
• Automated Hyperparameter Optimization: Tuning learning rates, num_leaves, and subsampling with Optuna.

Quick Start

import lightgbm as lgb
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split