a. Draw a two dimensional plot, in which the horizontal axis is x1 indicating the first feature value and the vertical axis is x2 indicating the second feature value. Then add 20 data points that are sampled from two classes: 10 data points in each of the positive (annotate as circles in the plot) and negative (annotate as crosses in the plot) classes. These 20 data points have to be plotted so that they are not linearly separable, and ensure that there are at least two misclassified data points using a linear classifier. b. Copy the plot you produced in (a), draw the decision boundary and margin with a brief explanation to illustrate how soft margin SVM works to classify the two classes. Explain the effects of any hyper-parameters used in the soft margin SVM algorithm.