Question: (10 marks) A normalized data set is stored in X -0.922 -1.618 X= 1.862 0.575 2.003 0.004 0.837 0.676 The SVD of X is X

 (10 marks) A normalized data set is stored in X -0.922-1.618 X= 1.862 0.575 2.003 0.004 0.837 0.676 The SVD of Xis X = UEV' with -0.659 10.498 0.565 -0.021 0.425 0.089 0.

(10 marks) A normalized data set is stored in X -0.922 -1.618 X= 1.862 0.575 2.003 0.004 0.837 0.676 The SVD of X is X = UEV' with -0.659 10.498 0.565 -0.021 0.425 0.089 0. 438 0.786 -0.608 -0.585 -0.168 0.498 ,I= diag (2 407, 2.217,0.225, 0.1001. -0.124 0.624 -0.679 0.366 Carry out dimension reduction with respect to the singular value threshold of = 0.3: find the image of x1.Given that E = diag ( 12. 407, 2.217, 0.225 , 0.100), we keep the first three singular values ( 12. 407, 2.217, 0.225) Since, They are greater than 0.3. Let's denote the reduced Singular value Matrix as Eyed and the Corresponding reduced matrices Ured and VredEred = diag ( 12.407, 2.217, 0.225) 0. 438 Ured - 0- 608 - 0.595 - 0.168 - O. 65 0.496 0 .565 - 0.021 Vred = O. 4 25 0.099 0.786 0.0 - 0. 124P 0. 624 - 0.679 0.366 The reduced matrix X, is obtained by Multiplying Ured by Ered and then multiplying by Vred X1 = Ured. Ered Vred calculate the product: XI 0.438 -0.608 -0. 595 . diag ( 12.407, 2. 217, 0.225). 0.168 0. 65 0.496 0.565 D. 425 0.099 0-786 0 .124 0.624 - 0. 679 - 0.021 0. 0 0. 366 Performing the matrix Multiplication will gives us the Image of X

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