lightgbm

name	lightgbm
description	LightGBM gradient boosting framework. Use for fast ML.

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

• Huge Datasets: Optimized for efficiency.
• Ranking: LGBMRanker is excellent for search/recommendation systems.

Core Concepts

Leaf-wise Growth

Grows the tree by splitting the leaf with max loss delta (creates deeper, unbalanced trees) vs Level-wise (balanced).

Histogram-based

Buckets continuous values into discrete bins for speed.

Best Practices (2025)

Do:

• Tune num_leaves: The most important parameter for controlling complexity.
• Use Categorical Features: Pass indexes of categorical columns directly.

Don't:

• Don't overfit: Leaf-wise growth overfits easily on small data. Limit max_depth.

References

• LightGBM Documentation