Ultimately, the goal of explainability in machine learning is to provide stakeholders with the ability to understand, validate, and trust the decisions made by machine learning models. It empowers users to identify potential biases, errors, or limitations in the models and promotes ethical and accou...
In machine learning, making a model interpretable for humans is becoming more relevant. Trust in and understanding of a model greatly increase its deployability. Interpretability and explainability are terms that refer to the understanding of a machine learning model. The relation between these two ...
参考 [^1]: C. Rudin,Stop explaining black-box machine learning models for high stakes decisions and use interpretable models instead(2019),https://arxiv.org/abs/1811.10154 [^2]: C. Molnar,Interpretable Machine Learning:A Guide for Making Black Box Models Explainable(2023), Chapter 3: Interpr...
参考 ^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....
The difference between machine learning explainability and interpretability 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 compli...
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?) ...
2]Machine Learning Explainability vs Interpretability: Two concepts that could help restore trust in ...
2]Machine Learning Explainability vs Interpretability: Two concepts that could help restore trust in ...
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 ...
Explanation methods that help users understand and trust machine-learning models often describe how much certain features used in the model contribute to its prediction. For example, if a model predicts a patient's risk of ...