Question: Use the Animals data set, depicted in Table 6.2, as a self set to generate 1000 detectors using the binary negative selection algorithm. Use the nonself set depicted in Table 6.3 to calculate the detection rate (DR) and the false alarm rate (FAR), described in Equation (6.6) and Equation (6.7), respectively, of the 1000 detectors generated.
Investigate the influence of different affinity measures (Hamming, rcontiguous and r-chunks) and affinity thresholds ε for the binary negative selection algorithm.
DR = TP/(TP+FN) (6.6)
FAR = FP/(FP+TN) (6.7)