Please only use numpy and matplot

Question 3. - Linear Discriminant Analysis: Consider the same categorical learning problem consisting of a data set with two labels: Label 1: Label 2: a) For each label above, the data follow a multivariate normal distribution Normal(i,) where the covariance is the same for both label 1 and for label 2. Fit a pair of Guassian discriminant functions to the labels by computing the covariances, means, and proportions of datapoints as discussed in the Linear Discriminant Analysis section. You may use a computer, but you should not use an LDA solver. You should report the values for i and . (Hint, since we use LDA, you need to compute using all data.) b) Give the formula for the line forming the discretion boundary. Plot the points and boundary. c) Use the QDA method for this question and obtain an quadratic boundary. (Hint, you need to calculate 1 and 2 separately. ) (d) Try quadratic LDA method for this question and obtain an quadratic boundary. (bonus)