# Questions tagged [vc-dimension]

VC-dimension (after Vapnik and Chervonenkis) is a measure of the power of a set of shapes (ranges) to realize subsets of points. VC-dimension is a vital analysis tool in the fields of machine learning and computational geometry.

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### representation of concept classes and pac learning

I was reading the book of Kearns and Vazirani and I didn't completely understand the following: Let C be a concept class and suppose we want to PAC learn C, they say first consider a larger ...
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### How to generalize VC dimension?

Let's try to generalize the $VC$-dimension (of the class of hyperplanes) to include accuracy/error. Let $S$ be a set of points in $R^d$ and $t$ in $[0,1]$. We say that the class of hyperplanes $t$-...
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### (eps,delta)-approx with VC-Dimension 1?

I have a domain $X$ and a set system $R$ on $X$, such that the sets in $R$ are one included in the other, that is, for any $A,B\in R$, either $A\subseteq B$ or $B\subseteq A$. The sets are not all ...
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### VC dimension of intersection of half-spaces

Define $$l_i(x) := \text{sgn} \left( w_i^\top x - b_i \right)$$ for $i=1,...,n$, where $x \in \mathbb{R}^d$. Then define the classifier $$g(x) := \max \{ l_1(x),..., l_n(x) \}$$ which represents ...
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### VC dimension for ellipsoidal classifiers

What is the VC dimension of $g: \mathbb{R}^n \times (\mathbb{R}^{n \times n} \times \mathbb{R}^n \times \mathbb{R}) \rightarrow \{-1,1\}$ defined as  g( x, (P_1,p_2,p_3), ) := \text{sgn} \left( x^\...
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### Do combinatorial discrepancy upper bounds lead to smaller $\epsilon$-nets (as with $\epsilon$-samples)?

An $\epsilon$-sample (or $\epsilon$-approximation) of a family of subsets $\mathcal{S}$ of a ground set $X$ is a subset $P \subseteq X$ which preserves relative sizes of sets up to $\epsilon$. I.e., ...
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### VC-Dimension and sample complexity dependent on size of subsets

I have a range space $(X,R)$, were $R$ is a collection of subsets of $R$ and I have an upper bound $d$ to the VC-dimension of $(X,R)$. Suppose for simplicity that $X$ is finite. Given $\delta\in(0,1)$ ...