Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. A Detection Error Tradeoff graph is a graphical plot of error rates for binary classification systems, plotting false reject rate vs. false accept rate. The x- and y-axes are scaled non-linearly by their Normal Deviates, yielding tradeoff curves that are more linear than ROC curves ...Täielik kirjeldus
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. A Detection Error Tradeoff graph is a graphical plot of error rates for binary classification systems, plotting false reject rate vs. false accept rate. The x- and y-axes are scaled non-linearly by their Normal Deviates, yielding tradeoff curves that are more linear than ROC curves, and spend most of the image area highlighting the differences of importance in the critical operating region. Classification in general is one of the problems studied in computer science, in order to automatically learn classification systems; some methods suitable for learning binary classifiers include the decision trees, Bayesian networks, support vector machines, and neural networks. Sometimes, classification tasks are trivial. Given 100 balls, some of them red and some blue, a human with normal color vision can easily separate them into red ones and blue ones. However, some tasks, like those in practical medicine, and those interesting from the computer science point-of-view, are far from trivial, and may produce faulty results if executed imprecisely.