The paper merges numerical and textual similarities in spectral clustering with a weight tuned on approved/rejected loan labels, yet the resulting 'recruitment implies lower risk' finding is contaminated by that same label information.
This method integrates numerical financial data with textual quarterly survey records by constructing an optimal similarity matrix
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Advanced spectral clustering for heterogeneous data in credit risk monitoring systems
The paper merges numerical and textual similarities in spectral clustering with a weight tuned on approved/rejected loan labels, yet the resulting 'recruitment implies lower risk' finding is contaminated by that same label information.