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  • 人工智能领域里的Interpretability和Explainability有什么区别吗？
    Interpretability指模型整体的可解释性，Explainability特指单个预测的可解释性（比如某次申请贷款被拒的原因）。 编辑于 2020-09-16 20:58 赞同 8 添加评论
  • 简单梳理一下机器学习可解释性（Interpretability） - 知乎
    关于机器学习可解释性（Interpretability），又或者是 XAI （Explainable Artificial Intelligence ）其实就是搞机器学习的研究者们始终存在的一个担忧：很多现在的 深度神经网络 没有办法以一种从人类角度完全理解模型的决策。我们知道现在的模型既可以完胜世界围棋
  • 机器学习模型Interpretability和Explainability之间的区别-CSDN博客
    尽管 Interpretability 和 Explainability 都被翻译成“可解释性”，但在机器学习领域，这是两个相关但又截然不同的概念。 本文回答以下问题： 如何区分Interpretability和Explainability; 为什么机器学习需要Interpretability或Explainability; 怎么提高机器学习模型的Interpretability
  • What Is AI Interpretability? - IBM
    AI interpretability focuses on understanding the inner workings of an AI model while AI explainability aims to provide reasons for the model's outputs Interpretability is about transparency, allowing users to comprehend the model's architecture, the features it uses and how it combines them to deliver predictions
  • What is Interpretability - Interpretable AI
    What is Interpretability? Learn how an algorithm is deemed to be interpretable, and how it is different to being explainable
  • Interpretability - Wikipedia
    In mathematical logic, interpretability is a relation between formal theories that expresses the possibility of interpreting or translating one into the other
  • Interpretable and explainable machine learning: A methods‐centric . . .
    Interpretability and explainability are crucial for machine learning (ML) and statistical applications in medicine, economics, law, and natural sciences and form an essential principle for ML model design and development
  • Introduction to Model Interpretability - Stanford University
    What is Interpretability? - Interpretability is NOT… - About making all models interpretable - About understanding every single bit about the model - Against developing highly complexmodels
  • Introduction to Interpretability and Explainability
    Interpretability: Interpretability, often used interchangeably with explainability, is the ability to explain or provide meaning to model predictions In particular, the goal of interpretability is to describe the structure of a model in a fashion easily understandable by humans
  • [机器学习]关于可解释性（interpretability）这个领域，看这里~ - 知乎
    笼统地说，interpretability关注于一个“how”，”怎么做到的“，力求解释某个方法为什么做出这样的决定或预测。对它具体的定义正是它的研究方向之一，我们稍后讲到，研究者们提出了不同的角度可以解释的东西，不断地丰富interpretability的定义。





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