# Two sets can be separated by a hyperplane iff their convex hulls do not intersect

So I am supposed to prove that two sets of points in $\mathbb{R}^n$ are linearly separable in an n-dimensional space if and only if their convex hulls do not intersect.

I understand the concept visually in 2 and 3 space, it's just that I'm confusing myself in circles on the proof. I'm trying to prove by contradiction. Here is what I have:

Suppose there are two sets of data points in $\mathbb{R}^n$ of size $N$, between finite points $a_j<b_j$ and $c_j<d_j$: $$\mathcal{S}_1: \{ p_i \big|\forall j,i,k: a_j < p_i < b_k\}, \mathcal{S}_2: \{ h_i \big|\forall j,i,k: c_j < h_i < d_k \}$$

With convex hulls $\mathcal{C}_1$,$\mathcal{C}_2$ such that: $$\mathcal{C}_1: \bigg\{\sum_{i=1}^N \omega_i p_i \bigg| \forall i: \omega_i > 0 \wedge \sum_{i=1}^N \omega_i =1\bigg\}, \mathcal{C}_2: \bigg\{\sum_{i=1}^N \sigma_i h_i \bigg| \forall i: \sigma_i > 0 \wedge \sum_{i=1}^N \sigma_i =1\bigg\}$$

Which simplifies to: $$\mathcal{C}_1: \{ \hat p \big|\forall i,\hat p,k: a_i < \hat p < b_k\}, \mathcal{C}_2: \{ \hat h \big|\forall i,\hat h,k: c_i < \hat h < d_k \}$$

Where: $$\mathcal{C}_1 \cap \mathcal{C}_2 \neq \emptyset \wedge \bigg(\exists f(x) \big| f(x) = \sum_{n=1}^N \lambda_n x_n \wedge \forall \hat p,x,\hat h: \hat p < f(x) < \hat h \bigg)$$

It follows from $\mathcal{C}_1 \cap \mathcal{C}_2 \neq \emptyset$ that: $$\exists \mathcal{D} \big| \mathcal{D}\subset\mathcal{C}_1,\mathcal{C}_2 \equiv \exists \hat p, \hat h \big| \hat p = \hat h$$

After this point I'm not sure what to do, I've tried converting it to vector math, but all I get is $p$ = $h$, and I don't know how to translate it to a contradiction. It's been a while since I've done any proof work, and I'm quite rusty. Is this heading in the right direction or should I trash it? Are my base assumptions correct? I would prefer direction, rather then answers because I want to pass this class.

update

I think i figured out my problem. I was defining the boundary with: $$\forall \hat p,x,\hat h: \hat p \leq f(x) \leq \hat h$$

But I realize that if the hulls have $x\in \mathcal{C}_1, \mathcal C_2$ they cannot have a boundary that separates a point from itself. So the boundary equation must be: $$\forall \hat p,x,\hat h: \hat p < f(x) <\hat h$$

I don't know how to fix your proof, but I think you are overformalizing things (all these sums, etc.). Below there's an alternate take. (Note: I assume that $C_1$ and $C_2$ are convex hulls of finite sets of points.)

If two convex hulls are lineary separable, then it means that there is a half-space $H$ such that $C_1 \subset H$ and $C_2 \subset H^c$. Obviously $C_1 \cap C_2 = \varnothing$ because $H \cap H^c = \varnothing$.

The other direction is more tricky. Let $d$ be the distance between $C_1$ and $C_2$, i.e. $$d = \inf_{p_1 \in C_1,\ p_2 \in C_2}|p_1 - p_2|.$$ We are in $\mathbb{R}^n$ so $C_1$ and $C_2$ are compact, and thus bounded and closed. Therefore there exists $p_1$ and $p_2$ such that $|p_1 - p_2| = d$. The convex hulls do not intersect, so $d > 0$. Let $\vec{v} = p_1 - p_2$. We will show that the unique hyperplane $P \perp \vec{v}$ such that $p_0 = p_2 + \frac{\vec{v}}{2} \in P$ separates $C_1$ and $C_2$. In order to do so, we will show that $\mathrm{dist}(C_i,P) = \frac{d}{2}$.

Proof by contradiction. Fix any $i \in \{1,2\}$. Because of existence of $p_i$ we know that $\mathrm{dist}(C_i,P) \leq \frac{d}{2}$. Let's assume that there exists $q_i$ such that $q_i \in C_i$ and $\mathrm{dist}(q_i,P) < \frac{d}{2}$. Convexity of $C_i$ implies that whole line $L_i = p_iq_i \subset C_i$, however,

• $L_i$ is not parallel to $P$,
• $p_i \in L_i$.

Therefore, $L$ is not tangent to ball $B = B(p_0, \frac{d}{2}) \ni p_i$ with center at $p_0$ and radius $\frac{d}{2}$. Hence, there exists $r_i \in L_i \cap B$ such that $\mathrm{dist}(r_i,p_0) < \frac{d}{2}$, so by triangle inequality we have $\mathrm{dist}(r_i,p_{3-i}) \leq \mathrm{dist}(r_i,p_0) + \mathrm{dist}(p_0,p_{3-i}) < d$, contradiction.

I think you should be able to use those ideas in your proof, let me know how it goes ;-)

• Can you expand more on the first part? To my understanding, the assumption should be that the sets themselves are linearly separable, not that their convex hulls are, which makes the argument non-trivial Mar 1 '19 at 15:56
• @DeanGurvitz You are correct that the first part should technically start form sets being linearly separable, rather than their convex hulls. On the other hand, $S_1 \subset H$ implies $C_1 = \operatorname{Conv}(S_1) \subset \operatorname{Conv}(H) = H$, so I don't see anything interesting there either. What would you like me to expand? Mar 1 '19 at 16:16
• Alright, it is fairly simple, but I think explicitly writing that the convex hull is a subset of the half-space would be beneficial here. Mar 1 '19 at 16:22

Following dtldarek's answer above:

Let the unit normal vector for the plane $P$ be $n=\dfrac{(p_0-p_1)}{\lVert p_0-p_1 \rVert}$.

Then for any $x\in C_1$, $n^{\rm T}(x-p_0)<-\dfrac{d}{2}<0$ because $\frac{d}{2}$ is the distance between $C_1$ and the plane P.

And for any $y \in C_2, n^{\rm T}(y-p_0)>\dfrac{d}{2}>0$.

So $n^{\rm T}x-n^{\rm T}p_0 <0$ and $n^{\rm T}y-n^{\rm T}p_0>0$.

This shows that the points in $C_1$ and $C_2$ are linearly separable.