Parent: #478
The 19-row canonical suite is excellent for reproducibility but one fixed shape can confuse interpreter/setup overhead with algorithmic throughput. Every canonical operation needs a scaling surface.
Build deterministic scaled fixtures covering relevant axes: n_samples, n_features, n_classes/clusters, n_estimators/depth, support vectors/kernel matrix size and batch size. Use logarithmic sizes from tiny through realistically large, with explicit memory-feasibility caps for O(n^2)/O(n^3) estimators.
Acceptance: each canonical operation has at least three meaningful sizes; slopes/complexity regimes are machine-readable; Pages can show crossover points; a Flow win at tiny size is not considered complete if it becomes a material loss at larger supported sizes; all scaled losses automatically link into #478.
Parent: #478
The 19-row canonical suite is excellent for reproducibility but one fixed shape can confuse interpreter/setup overhead with algorithmic throughput. Every canonical operation needs a scaling surface.
Build deterministic scaled fixtures covering relevant axes: n_samples, n_features, n_classes/clusters, n_estimators/depth, support vectors/kernel matrix size and batch size. Use logarithmic sizes from tiny through realistically large, with explicit memory-feasibility caps for O(n^2)/O(n^3) estimators.
Acceptance: each canonical operation has at least three meaningful sizes; slopes/complexity regimes are machine-readable; Pages can show crossover points; a Flow win at tiny size is not considered complete if it becomes a material loss at larger supported sizes; all scaled losses automatically link into #478.