classification


Data mining - error values interpretation


I am wondering how error measures in Weka is interpreted.
I understand how to interpret confusion matrix, kappa statics, ROC curve, and confusion matrix, but I cannot quite put the error measures into real life example.
I have a very vauge idea that error measures tell the magnitude of the error of prediction somewhat, but how exactly?
Could you please explain how error measures can fit in with real-life concrete example?

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