# Precision and recall in a multi-class classification system?

Having looked at Wikipedia and looked around here, I'm still not clear how to identify the true positives, true negatives, false positives and false negatives in the multi-label classification problem that I'm doing, so that I can calculate precision, recall and F-measure.

I have a few categories and a few hundred documents. Having trained an SVM to perform classification, I have the following data

document 1 | actual category, category assigned by SVM
document 2 | actual category, category assigned by SVM
...
document n | actual category, category assigned by SVM


The category assigned by the SVM is often the same as the actual category but not always. The true positives are when

actual category = category assigned by SVM


I guess false positives would be

actual category =/= category assigned by SVM


But I'm not sure about false positives or true negatives.

I feel like this may be a basic question but I can't find a clear (enough) example.

• – Gala Jul 21 '13 at 12:21