Tag: feature-engineering

All the articles with the tag "feature-engineering".

• Features and Overfitting: How a Model Memorizes, and How L1 and L2 Stop It

  Updated:24 Oct, 2026

  Give the router 379 features instead of one and it scores 100% on its training data and worse on new questions. Why that happens, why the weights run to infinity, how L2 and L1 penalties stop them (derived, with the soft-threshold that makes L1 exact zeros), why one well-chosen feature matches all 379, and how to tell a real difference from noise when the splits share data.

• Predicting Chess Outcomes: A Disciplined ML Walkthrough

  Updated:19 Oct, 2026

  Predicting who wins a Lichess blitz game from its opening, rebuilt end to end on 100,000 games. Against a rating curve refitted to the data, the opening adds nothing at move 3 and a Brier gain of about 0.002 at move 10, on all seven splits tried; a Stockfish evaluation makes it 0.0084. The method is the point: an audited dataset, a leakage contract enforced by tests, a baseline worth beating, and diagnostics before features.