In this question we explore classification in a problem involving two predictor features xA and xB and two classes, namely O (positive class) and (negative class). The dataset that will be used in this question is shown in Figure 1. Figure 1 Consider a family of linear classifiers defined by xTw=0, where w=[w0,wA,wB]T and x=[1,xA,xB]T. A sample xi such that xiTw>0 will be labelled as O, otherwise it will be labelled as . Use the dataset shown in Figure 1 to obtain the confusion matrix of the linear classifier defined by the coefficients vector w=[2,0,1]T. The values in the confusion matrix should represent counts