Enable Scan (x1,x2) are input features and target classes are either +1 or 1 as shown in the figure. [1+1+3=5] (a) What is the minimum number of hidden layers and hidden nodes required to classify the following dataset with 100% accuracy using a fully connected multilayer perceptron network? Step activation functions are used at all nodes. (b) Draw the minimal network architecture by organizing the nodes in each layer horizontally. Show the node representing x1 input feature at the left on the input layer. Organize the hidden nodes in ascending order of the bias value at that node. (c) Specify all weights and bias values at all nodes. Weights can be only 2.5,2.5 or 0 , and bias +ve/-ve multiples of 2.5