3. A multi-layer perceptron is tested with thirty observations from three classes C1, C2 and C3. Each class consists of ten observations. The following confusion matrix shows the results after testing the multi-layer perceptron with all the thirty observations. Actual class C C2 C2 C 7 2 0 C2 2 6 2 C3 1 2. 8 Assigned class TT For the case of class C1, determine the number of True Positives, False Positives, False Negatives and True Negatives. For the case of class C1, compute the following classification performance metrics: sensitivity, specificity and precision