#lightgbm

2 articles

01 ·Agents·★ MEMBER·PAPER·12 min read Paper Walkthrough: EarlyEval — Making Agent Evaluation Cheaper by Stopping Early One evaluation pass over an agentic benchmark costs hundreds of dollars. EarlyEval exploits the fact that an agent's ending is legible from its middle, halting runs to cut 13–26% of steps. Mechanism, numbers, and limits, straight from the paper. 02 ·Machine Learning Basics·FREE·PAPER·12 min read Decision Trees and Gradient Boosting — Still the Champion on Tabular Data On data made of rows and columns, ensembles of decision trees are still the first thing to reach for. From the intuition behind a single split to boosting, what XGBoost and LightGBM actually do, and why neural networks have not taken this territory — built up from nothing.