Two perceptron classifiers are trained to recognise the following classification of five patterns x with known class membership d.
0.4 1.0 —0.1 0.2 0.1 0.8 0.2 0.7 0.7 0.3 x1 = E.21, x2 = [ 0.5 , x3 = [ 0.3 , x4 = —0.81,x5 =1.5 0.3 0.7 0.3 0.9 0.9 0.2 —0.5 0.9 0.3 1.2
di=[1], d2=[-1], d3=[1], da=[-1], ds=[1]
Q1.1 [Discrete Perceptron Training] [25 marks]
The first classifier is a discrete perceptron as shown in Figure Q1.1. Assign “1” to all augmented inputs. For the training task of this classifier, the learning constant is c =2 and – 0.3350 0.1723 the discrete perceptron learning rule is used. The initial weight vector w1 = —0.2102 0.2528 —0.1133 0.5012
Assuming that the above training set may need to be recycled if necessary, calculate the final weight vector. Show that this weight vector provides the correct classification of the entire training set. Plot the pattern error curve and the cycle error curve for 10 cycles (50 steps).
