5. (15%) Consider the following data containing 5 training data points consisting of two features x...

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5. (15%) Consider the following data containing 5 training data points consisting of two features x and x (so here N = 5, p = 2), and two possible classes y E {0, +1}. Training Data X (Feature 1) X2(Feature 2) y #1 #2 #3 1 1 0 1 0 0 0 0 0 #5 #4 2 2 2 1 1 1 Our goal is to use LDA to obtain a classifier. a) (10 Points) Obtain the two discriminant functions do(x) and 8(x). b) (5 Points) Check that all the training points are classified correctly using the obtained discriminant functions do(x) and 8(x). (Note: You can use Matlab for computation) 5. (15%) Consider the following data containing 5 training data points consisting of two features x and x (so here N = 5, p = 2), and two possible classes y E {0, +1}. Training Data X (Feature 1) X2(Feature 2) y #1 #2 #3 1 1 0 1 0 0 0 0 0 #5 #4 2 2 2 1 1 1 Our goal is to use LDA to obtain a classifier. a) (10 Points) Obtain the two discriminant functions do(x) and 8(x). b) (5 Points) Check that all the training points are classified correctly using the obtained discriminant functions do(x) and 8(x). (Note: You can use Matlab for computation)