# Build confusion matrix for cross validated results? [closed]

I am using python , and I want to know how to build a confusion matrix after I have cross validated my dataset.

If build a confusion matrix at each fold then I have too many confusion matrices. I want one final CM with the right number of cases(not additive) as a final output.

I am currently using cross_val_score from scikit-learn to do my cross validation.

## closed as off-topic by Michael Chernick, kjetil b halvorsen, mkt, Peter Flom♦Jul 25 at 10:32

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You could compute all the confusion matrices, and then compute the mean and standard deviation for each entry. You could then report a summarized confusion matrix of means $$\pm$$ standard deviations.