Completing missing entries

$\frac{0\mathrm{.}2}{1\mathrm{.}0}$ point $($graded$)$

Now that we have a mixture model, how do we use it to complete a partially observed rating matrix? Derive an

expression for completing a particular row, say $x_C$ where the observed values are iinC.

In implement the function

that takes as input an incomplete data matrix $x$ as well as

a mixture model, and outputs a completed version of the matrix

Available Functions: You have access to the NumPy python library as $np,$ to the GaussianMixture class and

to typing annotation typing. Tuple as Tuple. You also have access to scipy.special.logsumexp as$""$nFills an incomplete matrix according to a mixture model X: $($n$,$ d$)$ array of incomplete data $($incomplete entries $=0)$Returns$"$##