datalets v0.7.0 — big-data controls

Controls born from a real 503k × 499 fit:

• Custom k grid: clusterer="kmeans", n_clusters=[4, 8] — the utility-scored search over exactly those configs. Combines with clusterer lists and "auto".
• exclude_candidates=["knn"]: keep a preset, drop a model. Typos warn instead of crashing an hours-long fit; excluding everything raises immediately.
• pca_components= (int or variance fraction): PCA-reduce the partition space — clustering/routing/silhouette in the reduced space, candidate models keep every feature. Recommended on wide data.
• Wide-data GMM handling: auto search switches mixtures to diagonal covariance above 100 features (full covariance is O(d²) per component per EM iteration); a named "gmm" warns instead of silently changing your choice.
• Advisory size limits added to knn (quadratic OOF scoring) and random_forest/extra_trees (multi-hour candidates at large n).

508 tests. CHANGELOG.md