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Accuracy of an estimator is the degree of closeness of the estimates to the true value. For a classifier, accuracy is the proportion of correct classifications. (This second usage is not good practice. See the tag wiki for a link to further information.)

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Is accuracy = 1- test error rate

In the case of classification, is a classifier's accuracy = 1- test error rate? I get that accuracy is $\frac{TP+TN}{P+N}$, but my question is how exactly are accuracy and test error rate related. …
micro_gnomics's user avatar