I'm working on a problem set. The class is called 'Algorithms for Inference'. In the definition of the problem, it says
$V$ is a set of vertices. An "independent set" can be represented as a binary vector of dimension $n=|V|$ with $I=[I_i]\in \{0,1\}^{|V|}$ representing the subset of vertices $\{i \in V : I_i = 1\}$ .
I don't understand what this at all, and want to kill myself. Could someone explain this to me as he/she would explain it to a 6-year old child? Thanks.
EDIT: Now I get the basic intuition now. The definition 'Independent set' is just a custom definition in my pset, and I didn't post it in the interest of conciseness. Just one more question, what does $I=[I_i]$ mean?
Lets say you have a set $V=\{1,2,\ldots,n\}$. It doesn't actually matter how the elements of $V$ are labelled, but it will be simpler to refer to them like this.
Imagine we have a subset $A\subset V$. Then some elements of $V$ are in the subset $A$, and the others are not. We could imagine associating to each number in $V$ a $1$ or a $0$, depending on whether it lies in $A$ or not.
For example, if $A=\{1,2,4\}$, then we would associate $1,2,4$ with the number $1$, but $3$ and $5,6,\ldots,n$ with the number $0$.
We could imagine arranging all of these ones and zeros into a column vector: for this choice of $A$ we would get:
$$\begin{pmatrix}1\\1\\0\\1\\0\\0\\\vdots\\0\end{pmatrix}$$
So for each subset of $A$, we get a corresponding column vector, whos coordinates are either 0 or 1. Note that $\{0,1\}^{|V|}$ represents the set of all $n$-coordinate column vectors.
You should also be aware that all of the above applies regardless of the type of subset you are looking at -- it doesn't even need to be independent (whatever that means in this context).