Summary
After reading this chapter, you should understand how to leverage traditional interpretation methods to more thoroughly assess predictive performance on a CNN classifier and visualize the learning process of CNNs with activation-based methods. You should also understand how to compare and contrast misclassifications and true positives with gradient-based and perturbation-based attribution methods. In the next chapter, we will study interpretation methods for multivariate time series and sensitivity analysis.
