Explaining Decision Optimization Recommendations

Explainability is a hot topic. Decision models are used to trigger recommendations such as “accept” or “refuse” a loan, but they also need to explain WHY they recommended certain decisions. Alain Chabrier from IBM DecisionOptimization team uses Portfolion Allocation problem to demonstrate how explainability works with Decision Optimization models. Link

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