Chapter 11, Anchors XAI

1. LIME explanations are global rules. (True|False)

   False. LIME explanations explain predictions locally.

2. LIME explains a prediction locally. (True|False)

   True.

3. LIME is efficient on all datasets. (True|False)

   False. An XAI tool is model-agnostic but not dataset-agnostic.

4. Anchors detect the ML model used to make a prediction. (True|False)

   False. Anchors are model-agnostic.

5. Anchors detect the parameters of an ML model. (True|False)

   False. Anchors are model-agnostic.

6. Anchors are high-precision rules. (True|False)

   True.

7. High-precision rules explain how a prediction was reached. (True|False)

   True.

8. Anchors do not apply to images. (True|False)

   False.

9. Anchors can display superpixels on an image. (True|False)

   True.

10. A model-agnostic XAI tool can run on many ML models. However,...