Confusion matrix, false negative

Solution 1

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.

Solution 2

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.

Regards -A

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Author by

Haritz

Updated on June 22, 2022