Consider the following training data consisting of three features X, X and x3 and the class attribute Y that I could be Red, White, or Black. (() 2 3 4 2 1 X5462 10 11 1 5 Black 1 Black 3 7 Black 9 5 White 10 0 White 12 1 White 1 1 1 White 1 0 8 Class Red Red Red 2 4 We run SGD to learn a logistic regression function for each of the following binary classification, and we get the respective learning parameters: For Red versus everything else (White and Black) classification, we get: 0o = -7.1, 0 = 1.4, 0 = 1.1. and 03 = 0 For White versus everything else (Red and Black) classification, we get: 0o = -8.15, 0 0.95, 0= 03=0 For Black versus everything else (Red and White) classification, we get: 00-8.75, 0=0.95, 02 = 0, 03 = 0 Consider the multi-classification problem of predicting whether a new data point (x.X2, X3) is Red, Black or White. 1. Write the expression for the logistic regression function for each of the given binary classification problems 2. Given a new data point (7.7.7), what would you classify it using the One-versus-All (OVA) algorithm? Explain.