Bias-Variance Tradeoff: A Property-Casualty Modeler’s Perspective

Abstract

The concept of bias-variance tradeoff provides a mathematical basis for understanding the common modeling problem of under-fitting vs. overfitting. While bias-variance tradeoff is a standard topic in machine learning discussions, the terminology and application differ from that of actuarial literature. In this paper we demystify the bias-variance decomposition by providing a detailed foundation for the theory. Basic examples, a simula-tion, and a connection to credibility theory are provided to help the reader gain an appreciation for the connections between the actuarial and machine learning perspectives for balancing model complexity. In addition, we extend the traditional bias-variance decomposition to the GLM deviance measure.

Volume
13
Issue
2
Year
2021
Categories
Financial and Statistical Methods
Statistical Models and Methods
Generalized Linear Modeling
Publications
Variance
Authors
Donald R Brockmeier
Joshua Brady

Keep up with the latest CAS news