automated classifier selection with ... - matlab & simulink

The ROC curve shows the true positive rate versus the false positive rate for different thresholds of the classifier output. For a perfect classifier, whose true positive rate is always 1 regardless of the threshold, AUC = 1. For a binary classifier that randomly assigns observations to classes, AUC = 0.5

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