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.