svm-crammer-singer-single-optimization

IN premise — entries/2026/06/21/wiki-Support_vector_machine-chunk-5.md

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

The Crammer-Singer method casts multiclass SVM as a single unified optimization problem rather than decomposing into multiple binary sub-problems.

Dependents

These beliefs depend on this one:

• IN svm-multiclass-requires-architectural-extension — SVMs' binary-native design requires substantial architectural extension for multiclass problems — decomposition into one-vs-all or one-vs-one subproblems, Platt scaling for probability calibration in OVA, or the unified Crammer-Singer formulation — with OVO generally outperforming OVA despite training more classifiers.