LATENT REFERENCES / TAG2
Regularization
Original title: 正則化 regularization
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In mathematics, statistics, and computer science, especially machine learning and inverse problems, regularization is a method of adding information to solve ill-posed problems or prevent overfitting. Introduced to penalize model complexity, it may penalize lack of smoothness or the magnitude of parameter norms.
数学・統計学・計算機科学において、特に機械学習と逆問題において、正則化とは、不良設定問題を解いたり過学習を防いだりするために、情報を追加する手法である。モデルの複雑さに罰則を科すために導入され、なめらかでないことに罰則をかけたり、パラメータのノルムの大きさに罰則をかけたりする。
Source updated 2023-07-03 · Snapshot 2026-10-08