Hi you have to divide results into four groups -
True class A (TA) - correctly classified into class A
False class A (FA) - incorrectly classified into class A
True class B (TB) - correctly classified into class B
False class B (FB) - incorrectly classified into class B
precision = TA / (TA + FA)
recall = TA / (TA + FB)
You might also need accuracy and F-measure:
accuracy = (TA + TB) / (TA + TB + FA + FB)
f-measure = 2 * ((precision * recall)/(precision + recall))
More here:
http://en.wikipedia.org/wiki/Precision_and_recall#Definition_.28classification_context.29