Statistics such as means and variances are estimated from training data and then applied unchanged to validation, test, and production inputs. This can improve optimization while avoiding leakage from held-out data.
Data normalization rescales or transforms features into a consistent numerical range or distribution.
Statistics such as means and variances are estimated from training data and then applied unchanged to validation, test, and production inputs. This can improve optimization while avoiding leakage from held-out data.