- Patent Title: Facilitating extraction of individual customer level rationales utilizing deep learning neural networks coupled with interpretability-oriented feature engineering and post-processing
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Application No.: US16113734Application Date: 2018-08-27
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Publication No.: US11295197B2Publication Date: 2022-04-05
- Inventor: Pavankumar Murali , Nianjun Zhou , Ta-Hsin Li , Pietro Mazzoleni , Wesley Gifford
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06Q30/02 ; G06N3/08

Abstract:
The disclosure relates to extraction of rationales for studied outcome. A method comprises: grouping features as expert to align with a set of operating practices; generating interpretable features using operating rules, combining with statistical dependence analysis to bin selected features to generate favorite practice actions; grouping features as expert that combine a subset of the interpretable features to align with a set of operating practices. The method can also comprise: using a neural network or deep learning component to quantify contribution of respective experts at a consumer level applying a generic additive approach; extracting feature importance at an individual consumer-level decomposed from expert level importance; evaluating alternative, what-if, scenarios through sensitivity analysis to identify favorite practice actions; consolidating a subset of the practice actions at client or stakeholder levels; and routing respective practice actions as a function of responsibility for the set of operating practices to stakeholders or consumers.
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