# XGBoost

13 Hacker News commenters recommended XGBoost and 0 criticized it, November 2025 to November 2026. It was recommended in 7 of 13 months. It meets the Hacker Approved badge rule.

**Verdict:** Recommended as a strong, fast baseline for tabular data that often beats neural networks. Main caveat: it needs a lot of feature engineering.

## Why people recommend it

- Beats neural networks on tabular data (4 comments): "I have never seen tabular transformer models beat xgboost/catboost in industrial context where datasets is gigantic." ([source](https://news.ycombinator.com/item?id=49874109)) "xgboost and lightgbm still outperformed anything NN based for tabular data" ([source](https://news.ycombinator.com/item?id=49171780)) "reach for XGBoost/LightGBM for tabular data is also good advice" ([source](https://news.ycombinator.com/item?id=47040556))
- Strong results on varied prediction tasks (4 comments): "I’ve gotten some really impressive results by just throwing xgboost on 25 classification related questions." ([source](https://news.ycombinator.com/item?id=50038325)) "TF-IDF with 1-gram features paired with XGBoost consistently emerged as the winner." ([source](https://news.ycombinator.com/item?id=45926398)) "xgboost model per timeseries has never been beaten before" ([source](https://news.ycombinator.com/item?id=50156050))

## Alternatives hackers recommend

- [PyTorch](https://hackerapproved.com/p/pytorch.md): 131 recommend
- [MLX](https://hackerapproved.com/p/mlx.md): 75 recommend
- [JAX](https://hackerapproved.com/p/jax.md): 49 recommend
- [OpenCV](https://hackerapproved.com/p/opencv.md): 46 recommend
- [tinygrad](https://hackerapproved.com/p/tinygrad.md): 40 recommend

## Cite as

Hacker Approved, "XGBoost", https://hackerapproved.com/p/xgboost/ (counts from 1,795,640 Hacker News comments, November 2025 to November 2026).