3. Consider the following dataset, with scalar features xi and binary class labels yi l: i123 456 xi | 0 | 1.3 | 2.1 | 2.8 | 4.2 | 5.7 Vi-1111 Consider a linear classifie r for this data of the form . where t is a threshold. For each threshold t, let J(t) denote the summed hinge loss, (a) Write a short python program to plot J(t) vs. t for 100 values of t in the interval E05 (b) Based on the plot, what is one value of t that minimizes J(t). c) For the value of t in part (b), find the corresponding slack variables (d) Which samples i violate the margin (ei > 0) and which samples i are misclassified (ej > 1) 3. Consider the following dataset, with scalar features xi and binary class labels yi l: i123 456 xi | 0 | 1.3 | 2.1 | 2.8 | 4.2 | 5.7 Vi-1111 Consider a linear classifie r for this data of the form . where t is a threshold. For each threshold t, let J(t) denote the summed hinge loss, (a) Write a short python program to plot J(t) vs. t for 100 values of t in the interval E05 (b) Based on the plot, what is one value of t that minimizes J(t). c) For the value of t in part (b), find the corresponding slack variables (d) Which samples i violate the margin (ei > 0) and which samples i are misclassified (ej > 1)