bayesian networks

DataFunTalk

Apr 28, 2023 · Artificial Intelligence

Causal Inference and Uplift Modeling for Insurance Recommendation and Explainability

This article explains how uplift sensitivity prediction, Bayesian causal networks, and decision‑path construction are applied to improve insurance product, coupon, and copy recommendations on the Fliggy platform, detailing modeling approaches, evaluation metrics, and practical outcomes of the causal inference framework.

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0 likes · 16 min read

Causal Inference and Uplift Modeling for Insurance Recommendation and Explainability

Model Perspective

Sep 15, 2022 · Artificial Intelligence

Unlocking Uncertainty: A Beginner’s Guide to Bayesian Networks

Bayesian Networks are powerful tools that translate complex probabilistic relationships into intuitive graph structures, enabling uncertainty reasoning, simplifying joint probability calculations, and forming the foundation for models such as Hidden Markov Models and Kalman filters, while also supporting data‑driven learning of network structures.

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0 likes · 2 min read

Unlocking Uncertainty: A Beginner’s Guide to Bayesian Networks