Whenever a binary classifier is used to provide decision support, it typically provides both a
label prediction and a confidence value. Then, the decision maker is supposed to use the …

Decision making or scientific discovery pipelines such as job hiring and drug discovery often
involve multiple stages: before any resource-intensive step, there is often an initial screening …

This paper provides both an introduction to and a detailed overview of the principles and
practice of classifier calibration. A well-calibrated classifier correctly quantifies the level of …

Multimodal machine learning has achieved remarkable progress in a wide range of
scenarios. However, the reliability of multimodal learning remains largely unexplored. In this …

Regression diagnostics meets forecast evaluation: conditional calibration, reliability diagrams,
and coefficient of determinatio Page 1 Electronic Journal of Statistics Vol. 17 (2023) 3226–3286 …

This paper provides both an introduction to and a detailed overview of the principles and
practice of classifier calibration. A well-calibrated classifier correctly quantifies the level of …

Many selection processes such as finding patients qualifying for a medical trial or retrieval
pipelines in search engines consist of multiple stages, where an initial screening stage …

Many large-scale recommender systems consist of two stages. The first stage efficiently
screens the complete pool of items for a small subset of promising candidates, from which …

Background: Despite an extensive network of primary care availability, Brazil has suffered
profoundly during the COVID-19 pandemic, experiencing the greatest sanitary collapse in its …

A major concern when dealing with financial time series involving a wide variety of market
risk factors is the presence of anomalies. These induce a miscalibration of the models used …