svm-feature-scaling-critical

IN premise — entries/2026/06/21/wiki-Support_vector_machine-chunk-6.md

Created 2026-06-21T09:55:54+00:00

Feature scaling (standardization) is critical for SVM performance and should always be applied before training.

Dependents

These beliefs depend on this one:

• IN svm-codified-practical-methodology — SVMs have an unusually prescriptive practical methodology for ML: standardize features first, default to RBF kernel, then grid-search C and gamma with cross-validation.