Hotspot anaysis highlights areas of an image of features in data that are important. It is often used in explainable AI applied to machine learning model such as a neural network; pixels or features are highlighted that are particularly critical in determining the output. These hotspots can sometimes be derived by modifying the algorithm used in the model, but perturbation methods can be used with a blax-box model.
Used on Chap. 21: pages 515, 525
Links:
alandix.com: XAI Kitbag
Key feature detection through perturbations