Augmenting trust and decision-making

Complex predictive machine learning models often lack transparency, resulting in low trust from these teams despite having high predictive performance. While many model interpretation approaches such as SHAP and LIME return top important features to help interpret model predictions, these top features may not be well-organized or intuitive to these teams.

To deal with this challenge, we developed Intellige, a customer-facing model explainer that creates digestible interpretations and insights reflecting the rationale behind model predictions.