From the theory of SVD’s we know G can be decomposed as a sum of rank-many rankone matrices. Suppose that G is approximated by a rank-one matrix sqT with s ∈ Rn and q ∈ Rm with non-negative components. Can you use this fact to give a difficulty score or rating? What is the possible meaning of the vector s? Note one can use the top singular value decomposition to get this score vector!

i think 1: 2

step-by-step explanation:

answer:

given the linear inequality :

add 2y to both sides we get;

simplify:

add 12 to both sides of an equation;

simplify:

divide both sides by 2 we get;

or

the related equation for the inequality equation [1] is;

y-intercepts defined as the graph crosses the y-axis.

substitute x =0 in [2] to solve for y;

y = 6

x-intercepts defined as the graph crosses the x-axis.

substitute value y = 0 to solve for x;

subtract 6 from both sides we get

multiply both sides by 2 we get;

or

x = -12

now, plot these point (0, 6) and (-12, 0) on graph as shown below and shade the graph below the solid line.

your answer is b.

x = 33.9

y = 65.6

step-by-step explanation:

step-by-step explanation:

its payment history because your score is mainly based on how consistent u are with your payment and if there on time. hope this : )