What evaluation classifiers? Precision & recall?
Hi,
I have some labeled data which classifies datasets as positive or negative. Now i have an algorithm that does the same automatically and I want to compare the results.
I was said to use precision and recall, but I'm not sure whether those are appropriate because the true negatives don't even appear in the formulas. I'd rather tend to use a general "prediction rate" for both, positives and negatives.
How would be a good way to evaluate the algorithm? Thanks!!
example: the data looks like this: {[some text, pos, pos]; [other txt, neg, pos]; [whatever, neg, neg]; [littlepny, pos, neg]} ...so its like some data, then the manual annotation, then the program's output.