Global Surrogate Models in Machine Learning
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Questions and Answers

What is the purpose of a global surrogate model?

  • To simulate the black box model
  • To approximate the predictions of a black box model and provide interpretability (correct)
  • To replace the black box model
  • To train the black box model

    • What distinguishes surrogate models used in engineering from those used in interpretable machine learning?

  • The interpretability of the model
  • The underlying model is a machine learning model and the surrogate model must be interpretable (correct)
  • The time it takes to train the model
  • The complexity of the model

    • Why might a surrogate model be used in engineering?

  • If the data is too large
  • If the model needs to be interpretable
  • If an outcome is difficult to measure (correct)
  • If the model is too complex

    • What is a characteristic of a surrogate model in machine learning?

    <p>It approximates the predictions of the underlying model and is interpretable</p> Signup and view all the answers

    What is a common use of surrogate models?

    <p>To replace expensive or time-consuming measurements</p> Signup and view all the answers

    What is a barrier to the adoption of machine learning?

    <p>The lack of interpretable models</p> Signup and view all the answers

    What is the focus of the book?

    <p>On model-agnostic methods for interpreting black box models</p> Signup and view all the answers

    Which of the following methods is not used for interpreting black box models according to the book?

    <p>Genetic algorithms</p> Signup and view all the answers

    What does the book say about the interpretation methods?

    <p>They are explained in depth and discussed critically</p> Signup and view all the answers

    Which of the following models is not mentioned in the book as a simple, interpretable model?

    <p>Support Vector Machines</p> Signup and view all the answers

    Which of the following models is not interpretable on a modular level according to the text?

    <p>k-nearest neighbors method</p> Signup and view all the answers

    Which of the following is not a property of an interpretable model?

    <p>The model can predict future outcomes</p> Signup and view all the answers

    What does the text suggest about the content available on interpretable models?

    <p>There is a ton of books, videos, tutorials, papers and more material available</p> Signup and view all the answers

    Which of the following models is not mentioned in the text as being discussed in more detail in the book?

    <p>Neural networks</p> Signup and view all the answers

    What is a characteristic of a model that is linear according to the text?

    <p>The association between features and target is modelled</p> Signup and view all the answers

    What is the primary objective of Explainable AI (XAI)?

    <p>To help users understand the reasoning behind AI decisions</p> Signup and view all the answers

    What does Explainable AI (XAI) contrast with in machine learning?

    <p>Black box concept</p> Signup and view all the answers

    What can Explainable AI (XAI) potentially be an implementation of?

    <p>The social right to explanation</p> Signup and view all the answers

    What does Explainable AI aim to unveil?

    <p>The information the actions are based on</p> Signup and view all the answers

    What can Explainable AI (XAI) help to generate?

    <p>New knowledge</p> Signup and view all the answers

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