Figure 2.

Diagram of the Locally-Interpretable Model-agnostic Explanations (LIME) algorithm in four steps. To generate explanations for a classification, the given image was first divided into superpixels. A distribution of perturbed images was generated and passed through the original prediction model to compute the classification probabilities. These probabilities and perturbed images were presented to a regression model that estimated the positive or negative contribution of each superpixel to the classification. The regression weights were then plotted in a blue-red color map.