Evaluate the impact of an AI application used in the real world. (case study) : Working with X-Ray images: Case Study -

The video tutorial discusses the limitations of using accuracy as a metric and introduces AUC as a better alternative. It highlights the problem of class imbalance affecting AUC and proposes a solution using weighted cross entropy. The tutorial explains how to implement this solution by penalizing misclassifications of low-prevalence classes more heavily, thereby improving model performance. The video concludes with a plan to test the new approach in a subsequent lecture.

Explain how misclassification penalties are applied in the context of class imbalance.

What changes are made to the loss function when implementing weighted cross entropy?

What are the expected outcomes of applying the new cross entropy function in model training?