Persist the fitted feature schema across evaluate, predict, serve, and export

Normalized profile

What this task asks for

Persist and reuse the fitted feature schema so evaluation, prediction, serving, and export all apply the same canonicalized inputs. When fit runs with dataset.features configured, the selected raw feature schema is not persisted. After fit, write feature_schema.joblib in the results directory and record feature_schema_path, input_features, dropped_features, and duplicate_feature_aliases in description.json. These rules must hold for single-target, multi-target, and clustering models. Extra raw columns must be ignored. Missing required selected features must raise an error naming them. If multiple duplicate sources are supplied they must agree row-wise for every row or raise an error naming the conflicting columns.