This is a two-class problem, and we draw 100 points from each class in the following...

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This is a two-class problem, and we draw 100 points from each class in the following way. Generate 100 observations from a bivariate Gaussian distribution N (₁,₁) with μ₁ = (2, 1)¹ and Σ₁ = I (the identity matrix), and label them as Green. Generate 100 observations from a bivariate = (1, 2) and E2 Gaussian distribution N(2, 2) with 2 and label them as Red. = I, (i) Write R code to generate the training data. Set the seed with set.seed (2020) before calling the random number generation function. (ii) Draw the scatter plot of the training data, using different labels/colors for two classes. (iii) Generate a test set, with 500 observations from each class, using set.seed (2019). Save the data set for Question 4. This is a two-class problem, and we draw 100 points from each class in the following way. Generate 100 observations from a bivariate Gaussian distribution N (₁,₁) with μ₁ = (2, 1)¹ and Σ₁ = I (the identity matrix), and label them as Green. Generate 100 observations from a bivariate = (1, 2) and E2 Gaussian distribution N(2, 2) with 2 and label them as Red. = I, (i) Write R code to generate the training data. Set the seed with set.seed (2020) before calling the random number generation function. (ii) Draw the scatter plot of the training data, using different labels/colors for two classes. (iii) Generate a test set, with 500 observations from each class, using set.seed (2019). Save the data set for Question 4.

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