Consider the Dataset for the classification problem defined below: X_train = [ -1 0 -1 0 y_train = [0 0 1 1] 0
a. Design a single-neuron perceptron to solve this problem. Design the network graphically, by choosing weight vectors (W) and biases
(b) that are orthogonal to the decision boundaries (meaning that you have to find the values of the parameters by trial and error of by mathematical formula). b. Test your solution with all four input/training vectors. c. Classify the following input/test vectors with your solution. X_test= [1 0 -2 1 1 1] co y_test = [?? ? ?] d. Which of the vectors in part
(C) will always be classified the same way, regardless of the solution values for Wand b? Which may vary depending on the solution? Why?