Plot confusion matrix not from predictions but from actual confusion matrix about scikit-plot

[jake-mason]

What prompts you to represent a continuous outcome/prediction ($ amount) in terms of a confusion matrix (meant for binary or categorical modeling tasks)? It seems to me the output of a confusion matrix with even tens of different categories represented would be difficult to understand, let alone potentially thousands of categories.

I assume you're trying to understand your model's performance across the entire dollar range, to see where there may be gaps. Have you tried a residual plot (i.e. plotting predicted $ amount on the x-axis, and the error on the y-axis?

I suppose you could try binning your $ amounts to reduce the cardinality in the predictions/actual outcomes but that seems arbitrary and roundabout.