Consider a single-neuron perceptron with a hard limit transfer function (hardlim). Input Hard Limit Layer W a = hardlim(n) RX1 5x 1 5X R SX 1 b SX1 S a = hardlim (Wp+b) n = Wp+b The hardlim transfer function is defined as: | a = hardlim(n) = 1 1 if n20 0 otherwise. Using the single-neuron perceptron, solve the three simple classification problems (a), (b), and (C), shown in the figure below: -.L. (a) (b) (c) 1. Draw a decision boundary. 2. Find the weight and bias values that result in a single-neuron perception with the chosen decision boundaries. Observe the fitting model data to a training data set. 3. How would you find the variance for this problem case? 4. Check your solution (post-training data) against the original points. 5. Use Python and the corresponding libraries to automate the testing process, and to try new points. Submit the source code and how you automated the testing. Complete this by hand and then write a code to compute the different points for (a), (b) and (C)