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.
Let say I have a trained network that does the classification.
Now I want to see how often the classifier makes false positive respectively false negative predictions by grouping them accordingly to the gender feature.
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.
