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I read that as the 6 being a false positive on the confusion matrix, but a false negative on the error histogram.
Am I reading the charts incorrectly? (That is highly likely but I don't see how I can be.)
Otherwise the simplest explanation is that the confusion matrix has the true class on the X-axis and the predicted class on the Y axis.
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I read that as the 6 being a false positive on the confusion matrix, but a false negative on the error histogram.
Am I reading the charts incorrectly? (That is highly likely but I don't see how I can be.)
Otherwise the simplest explanation is that the confusion matrix has the true class on the X-axis and the predicted class on the Y axis.
The easiest way to see this is to run the PyCaret Binary Classification tutorial and plot an error histogram after the confusion matrix.
https://github.com/pycaret/pycaret/blob/master/tutorials/Tutorial%20-%20Binary%20Classification.ipynb
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