On the Value of ML Models

• URL: http://arxiv.org/abs/2112.06775v1
• Date: Mon, 13 Dec 2021 16:32:08 GMT
• Title: On the Value of ML Models
• Authors: Fabio Casati, Pierre-Andr\'e No\"el and Jie Yang
• Abstract summary: We argue that, when establishing and benchmarking Machine Learning (ML) models, the research community should favour evaluation metrics that better capture the value delivered by their model in practical applications. For a specific class of use cases -- selective classification -- we show that not only can it be simple enough to do, but that it has import consequences and provides insights what to look for in a good'' ML model.
• Score: 7.301530330533432
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We argue that, when establishing and benchmarking Machine Learning (ML) models, the research community should favour evaluation metrics that better capture the value delivered by their model in practical applications. For a specific class of use cases -- selective classification -- we show that not only can it be simple enough to do, but that it has import consequences and provides insights what to look for in a ``good'' ML model.

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