Confusion matrix, false negative
True positives are cases predicted positive which are actual positive
False positives are cases predicted positive which are actual negative (false alarms)
False negatives are cases predicted negative which are actual positive (missed cases)
True negatives are cases predicted negative which are actual negative
Just count these up and put them in your confusion matrix. If you want rates, Wikipedia has a concise description.
You question may be ill-posed, but let me see if I can provide some thoughts.
Does this Example work?
Matlab even has a Command with examples.
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Haritz 1 day
I would like to know how to calculate the false negative, the true negative, the false positive and the true positive to form a confusion matrix. A numeric example would clear all doubts I think. Thanks.