Shared Canonical Component Removal Beyond Expert Views
The Shared Canonical Component Removal (SCCR) framework audits raw model embeddings by comparing them to an expert-derived view. It selectively removes redundant information from the raw data that is already explained by the expert view, preserving complementary predictive signals. This method uses regularized Canonical Correlation Analysis to isolate unique domain knowledge.