4) a) Write the algorithm (in steps )used in Self Organizing Feature Map (SOFM) to update the weights of the Feature map. b) Comment about the selection of the learning parameter (n) and the neighborhood function (A) as the iteration increases. c) Our aim is to classify the three classes C ,C, and C,. To achieve this goal, we used the self organizing lattice network structure that is represented in two dimensional (in 3x3 matrix) form. After 6000 iterations, the centers and also which class is represented by each center is found and given below. Using these centers, find which class each testing data element of T belongs to. (-1.4 0.9 1.0 1.2 -0.3 (1.1 1.4 (0.7 (1.6)|fc c 1.7 || CC, JandT = (1.4)|LC; C; C, 0.4 -0.45 1.1 1.55 0.6 -0.2 -1.2 0.1) -1.1 - 1.0 0.95) -1.0 (0.1) (-0.9) 1.2 1.2 (1.5) (-0.2 1.05 1.05 -1.8 -0.7 (-0.5 1.6 1.3