Background: Sensitive and interpretable machine learning (ML) models can provide valuable assistance to clinicians in managing patients with heart failure (HF) at discharge by identifying individual factors associated with a high risk of readmission. In this cohort study, we delve into the factors ...
^W. J. Murdoch, et al., 'Definitions, methods, and applications in interpretable machine learning', PNAS, vol. 116, no. 44, 2019. ^A. Cicirello, Physics-enhanced machine learning: a position paper for dynamical systems investigations. ...
In the context of machine learning and artificial intelligence, explainability and interpretability are often used interchangeably. While they are very closely related, it’s worth unpicking the differences, if only to see how complicated things can get once you start digging deeper into machine learni...
This paper examines the cost of explainability in machine learning models for credit scoring. The analysis is conducted under the constraint of meet- ing the regulatory requirements of the European Central Bank (ECB), using a real-life dataset of over 50,000 credit exposures. We compare the ...
参考: https://www.kaggle.com/learn/machine-learning-explainability 这个课程将讲解如何从复杂的机器学习模型中解释这些发现。 模型认为数据中的哪些特征是最重要的? 对于来自模型的任何单个预测,数据中的每个特性如何影响该特定预测 每个特性如何影响模型的整体预测(当考虑大量可能的预测时,它的典型影响是什么?) ...
Nasopharyngeal cancer (NPC) has a unique histopathology compared with other head and neck cancers. Individual NPC patients may attain different outcomes. This study aims to build a prognostic system by combining a highly accurate machine learning model (
It also monitors inferences that the models make in production for bias or feature attribution drift. The fairness and explainability functions provided by SageMaker AI Clarify help you build less biased and more understandable machine learning models. It also provides tools to help you generate model...
2]Machine Learning Explainability vs Interpretability: Two concepts that could help restore trust in ...
Explainability in artificial intelligence (AI), and in particular in machine learning (ML), is a rapidly growing research area today. This is due to multiple factors stemming from the needs of different stakeholders in the development and use of ML techniques. These include developers (research an...
Visualization toolkit for neural networks in PyTorch! Demo --> visualizationmachine-learningdeep-learningcnnpytorchneural-networksinterpretabilityexplainability UpdatedSep 21, 2023 HTML Papers about explainability of GNNs machine-learningdeep-learninggraph-miningexplainable-aixaigraph-neural-networksexplainability ...