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Published in Transactions on Machine Learning Research (07/2024)Nonsensitive Learning to Defer to Multiple Experts with Workload Constraints Jean V. Alvesjean.alves@feedzai.comFeedzaiDiogo Late FeedzaiSrgio

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What is cost-sensitive learning to defer?

Cost-sensitive learning to defer refers to a methodology in machine learning that prioritizes minimizing the costs associated with misclassification when making predictions, allowing certain instances to be deferred for later evaluation based on their cost implications.

Who is required to file cost-sensitive learning to defer?

Organizations or individuals engaged in projects that utilize cost-sensitive learning models may be required to file cost-sensitive learning to defer, particularly if they involve financial implications or regulatory compliance.

How to fill out cost-sensitive learning to defer?

To fill out a cost-sensitive learning to defer form, provide detailed information about your project's objectives, the associated costs for misclassification, any adaptive learning strategies, and the anticipated outcomes for different scenarios.

What is the purpose of cost-sensitive learning to defer?

The purpose of cost-sensitive learning to defer is to optimize decision-making processes where the costs of errors are significantly different, enabling more efficient resource allocation and better outcomes in predictive modeling.

What information must be reported on cost-sensitive learning to defer?

Information that must be reported includes the model specifics, cost estimation for different types of errors, assumptions made during the model design, and the expected impact of deferring certain instances.