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Confusion Matrix Description A confusion matrix is a visualization tool typically used in supervised learning. Each column of the matrix represents the instances in a predicted class, while each row represents the instances in an actual class. One benefit of a confusion matrix is that it is easy to see if the system is confusing two classes (i.e. commonly mislabelling one as an other). In the example confusion matrix below, of the 8 actual cats, the system predicted that three were dogs, and of the six dogs it predicted that one was a rabbit and two were cats. We can see from the matrix that the system in question has trouble distinguishing between cats and dogs, but can make the distinction between rabbits and other types of animals pretty well. | xample confusion matrix | | !Cat !Dog !Rabbit | | at | 5 | 3 | 0 | | og | 2 | 3 | 1 | | abbit | 0 | 2 | 11 | External Links Description at the University of Regina
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