I have a dataset that consists of different features, like "gender".
The task of the model is to determine if the annual income is above or below 50k. It is the "Adult income dataset" from: https://www.kaggle.com/datasets/wenruliu/adult-income-dataset
Let say I have a trained network that does the classification.
Now I want to see how often the classifier make false positive respectively false negative predictions w.r.t "gender".
The basic idea is a confusion matrix of some sorts, but not a matrix of class to class but class to feature. The image below illustrates the result I would like to have.
