Some models are useful, but for how long?: A decision theoretic approach to choosing when to refit large-scale prediction models
模型能用多久？选择大型预测模型重拟合时机的决策理论方法
Large-scale prediction models using tools from artificial intelligence (AI) or machine learning (ML) are increasingly common across a variety of industries and scientific domains. Despite their effectiveness, training AI and ML tools at scale can cost tens or hundreds of thousands of dollars (or more); and even after a model is trained, substantial resources must be invested to keep models up-to-date. This paper presents a decision-theoretic framework for deciding when to…