In the field of artificial intelligence, a confusion matrix is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one (in unsupervised learning it is usually called a matching matrix). Each column of the matrix represents the instances in a predicted class, while each row represents the instances in an actual class. The name stems from the fact that it makes it easy to see if the system is confusing two classes (i.e. commonly mislabeling one as another). Outside artificial intelligence, the confusion matrix is often called the contingency table or the error matrix.
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Famous quotes containing the words confusion and/or matrix:
“The confusion is not my invention. We cannot listen to a conversation for five minutes without being aware of the confusion. It is all around us and our only chance now is to let it in. The only chance of renovation is to open our eyes and see the mess. It is not a mess you can make sense of.”
—Samuel Beckett (1906–1989)
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—Salvador Minuchin (20th century)