What is recall on positive and negative class?

Question

Machine learning

A data set of 200 examples and two class labels (for example, positive and negative) was divided into a training set of 100 examples and a test set of 100 examples. The 1-NN model was applied and achieved 80% accuracy for both positive and negative classes. In addition, 80 test cases were classified as positive and 20 as negative.

What is recall on positive and negative class?

Now suppose that 60 test cases that were predicted to be positive were randomly copied (duplicated) from the training set. These 60 examples were identified and subsequently removed from the test set.

What is the recall of the positive and negative class for the new test class, which now contains only 40 examples?