Paper 2, Section II, J

Mathematics of Machine Learning | Part II, 2020

(a) Let F\mathcal{F} be a family of functions f:X→{0,1}f: \mathcal{X} \rightarrow\{0,1\}. What does it mean for x1:n∈Xnx_{1: n} \in \mathcal{X}^{n} to be shattered by F\mathcal{F} ? Define the shattering coefficient s(F,n)s(\mathcal{F}, n) and the VCV C dimension VC⁡(F)\operatorname{VC}(\mathcal{F}) of F\mathcal{F}

Let

A={∏j=1d(−∞,aj]:a1,…,ad∈R}\mathcal{A}=\left\{\prod_{j=1}^{d}\left(-\infty, a_{j}\right]: a_{1}, \ldots, a_{d} \in \mathbb{R}\right\}

and set F={1A:A∈A}\mathcal{F}=\left\{\mathbf{1}_{A}: A \in \mathcal{A}\right\}. Compute VC⁡(F)\operatorname{VC}(\mathcal{F}).

(b) State the Sauer-Shelah lemma.

(c) Let F1,…,Fr\mathcal{F}_{1}, \ldots, \mathcal{F}_{r} be families of functions f:X→{0,1}f: \mathcal{X} \rightarrow\{0,1\} with finite VC dimension v⩾1v \geqslant 1. Now suppose x1:nx_{1: n} is shattered by ∪k=1rFk\cup_{k=1}^{r} \mathcal{F}_{k}. Show that

2n⩽r(n+1)v.2^{n} \leqslant r(n+1)^{v} .

Conclude that for v⩾3v \geqslant 3,

VC(∪k=1rFk)⩽4vlog⁡2(2v)+2log⁡2(r)\mathrm{VC}\left(\cup_{k=1}^{r} \mathcal{F}_{k}\right) \leqslant 4 v \log _{2}(2 v)+2 \log _{2}(r)

[You may use without proof the fact that if x⩽α+βlog⁡2(x+1)x \leqslant \alpha+\beta \log _{2}(x+1) with α>0\alpha>0 and β⩾3\beta \geqslant 3, then x⩽4βlog⁡2(2β)+2αx \leqslant 4 \beta \log _{2}(2 \beta)+2 \alpha for x⩾1x \geqslant 1.]

(d) Now let B\mathcal{B} be the collection of subsets of Rp\mathbb{R}^{p} of the form of a product ∏j=1pAj\prod_{j=1}^{p} A_{j} of intervals AjA_{j}, where exactly d∈{1,…,p}d \in\{1, \ldots, p\} of the AjA_{j} are of the form (−∞,aj]\left(-\infty, a_{j}\right] for aj∈Ra_{j} \in \mathbb{R} and the remaining p−dp-d intervals are R\mathbb{R}. Set G={1B:B∈B}\mathcal{G}=\left\{\mathbf{1}_{B}: B \in \mathcal{B}\right\}. Show that when d⩾3d \geqslant 3,

VC(G)⩽2d[2log⁡2(2d)+log⁡2(p)]\mathrm{VC}(\mathcal{G}) \leqslant 2 d\left[2 \log _{2}(2 d)+\log _{2}(p)\right]

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