VC Dimension Calculation for Intervals As i See in ML Course a VC dimension calculation is very theoretical. 

What is the VC-dimension of intervals in R? 

The target function is specifieed by an interval, and labels any example positive i it lies inside that interval.

Answers:

VC-dim = 2. A set of two points can be shattered, since there's only a single block of positive examples that could lie within the interval. But no set of 3 points can be shattered, because it can not be labeled in alternating +; - ; + order.

so i'm get stuck with meaning of interval. 

for example, it means {(a, b) | "a is lower than b", a,b is real number} has VC-dim = 2?

Any idea or solution would be highly appreciated.
Yes, an open interval in $\mathbb{R}$ is defined as $(a,b) = ]a,b[ = \left \{ x \in \mathbb{R}|\,a&lt;x&lt;b\right \} $. It has two parameters $a$ and $b$. The sets of all open intervals, i.e. $\left \{  \left \{ x \in \mathbb{R}|\,a&lt;x&lt;b\right \} | a,b \in \mathbb{R}\right\}$ has a VC dimension of 2 for the reason you mention. Keep in mind that the VC dimension of a hypothesis set $H$ is the most points $H$ can shatter.). To put it graphically:



(image from CalTech's free machine Learning online course by Yaser Abu-Mostafa Learning from Data)