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    The VC-Dimension of Similarity Hypotheses Spaces

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    Given a set XX and a function h:X⟢{0,1}h:X\longrightarrow\{0,1\} which labels each element of XX with either 00 or 11, we may define a function h(s)h^{(s)} to measure the similarity of pairs of points in XX according to hh. Specifically, for h∈{0,1}Xh\in \{0,1\}^X we define h(s)∈{0,1}XΓ—Xh^{(s)}\in \{0,1\}^{X\times X} by h(s)(w,x):=1[h(w)=h(x)]h^{(s)}(w,x):= \mathbb{1}[h(w) = h(x)]. This idea can be extended to a set of functions, or hypothesis space HβŠ†{0,1}X\mathcal{H} \subseteq \{0,1\}^X by defining a similarity hypothesis space H(s):={h(s):h∈H}\mathcal{H}^{(s)}:=\{h^{(s)}:h\in\mathcal{H}\}. We show that vcβˆ’dimension(H(s))∈Θ(vcβˆ’dimension(H)){{vc-dimension}}(\mathcal{H}^{(s)}) \in \Theta({{vc-dimension}}(\mathcal{H})).Comment: 6 page
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