A tutorial on calibration measurements and calibration models for clinical prediction models
Our primary objective is to provide the clinical informatics community with an introductory
tutorial on calibration measurements and calibration models for predictive models using …
tutorial on calibration measurements and calibration models for predictive models using …
A survey on learning to reject
Learning to reject is a special kind of self-awareness (the ability to know what you do not
know), which is an essential factor for humans to become smarter. Although machine …
know), which is an essential factor for humans to become smarter. Although machine …
Classifier calibration: a survey on how to assess and improve predicted class probabilities
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 …
practice of classifier calibration. A well-calibrated classifier correctly quantifies the level of …
Classifier calibration: a survey on how to assess and improve predicted class probabilities
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 …
practice of classifier calibration. A well-calibrated classifier correctly quantifies the level of …
Hospital acquired pressure injury prediction in surgical critical care patients
J Alderden, KP Drake, A Wilson, J Dimas… - BMC medical informatics …, 2021 - Springer
Background Hospital-acquired pressure injuries (HAPrIs) are areas of damage to the skin
occurring among 5–10% of surgical intensive care unit (ICU) patients. HAPrIs are mostly …
occurring among 5–10% of surgical intensive care unit (ICU) patients. HAPrIs are mostly …
Distribution reliability assessment-based incremental learning for automatic target recognition
S Dang, Z Cui, Z Cao, Y Pi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
To rapidly improve the automatic target recognition (ATR) system when new unknown
samples are constantly captured, it is necessary to examine the existing training samples …
samples are constantly captured, it is necessary to examine the existing training samples …
An experimental investigation of calibration techniques for imbalanced data
L Huang, J Zhao, B Zhu, H Chen, SV Broucke - Ieee Access, 2020 - ieeexplore.ieee.org
Calibration is a technique used to obtain accurate probability estimation for classification
problems in real applications. Class imbalance can create considerable challenges in …
problems in real applications. Class imbalance can create considerable challenges in …
Shape-constrained regression using sum of squares polynomials
We present a hierarchy of semidefinite programs (SDPs) for the problem of fitting a shape-
constrained (multivariate) polynomial to noisy evaluations of an unknown shape-constrained …
constrained (multivariate) polynomial to noisy evaluations of an unknown shape-constrained …
Advancing neural network calibration: The role of gradient decay in large-margin Softmax optimization
S Zhang, L Xie - Neural Networks, 2024 - Elsevier
This study introduces a novel hyperparameter in the Softmax function to regulate the rate of
gradient decay, which is dependent on sample probability. Our theoretical and empirical …
gradient decay, which is dependent on sample probability. Our theoretical and empirical …
Lifetime estimation based health index and conditional factor for underground cable system
T Somsak, T Suwanasri, C Suwanasri - Energies, 2021 - mdpi.com
In this paper, a lifetime estimation method for underground cable systems is proposed by
combining a health index (HI) and conditional factor (CF). The underground cable system …
combining a health index (HI) and conditional factor (CF). The underground cable system …