Im my algorithm, I am working with Singular Value Decomposition (SVD).
I have an input matrix $A_{in} \in \{0,1\}^{(m * n)} $, made by $n$ rows and $m$ colums. All the entries are 0 or 1.
I decompose it in $A = U * \Sigma * V^{T}$
After choosing a proper truncation level $k$, I construct an output matrix $A_{out} \in \mathbb{R}$, this way:
$ U_{k} * \Sigma_{k} * \; V^{T}_{k} = A_{out}$
All the $A_{out}$ entries are real valued.
What is the meaning of each real value?
Is it the likelihood that the element is near to 1.0 in the reconstruction?
Or are the real values just to create an order, from the less likely to the most likely?