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Definition
The shattering coefficient \(S_{\mathcal{F}}(n)\) is a function that measures the size of a function class \(\mathcal{F}\) when its functions \(f : \mathcal{X} \rightarrow \mathbb{R}\) are restricted to sets of points \(\mathbf{x} = (x_{1},\ldots,x_{n}) \in \mathcal{X}^{n}\) of size n. Specifically, for each \(n \in \mathbb{N}\) the shattering coefficient is the maximum size of the set of vectors \(\mathcal{F}_{\mathbf{x}} =\{ (f(x_{1}),.\ldots,f(x_{n})) : f \in \mathcal{F}\}\subset \mathbb{R}^{n}\) that can be realized for some choice of \(\mathbf{x} \in \mathcal{X}^{n}\). That is,
The shattering coefficient of a hypothesis class \(\mathcal{H}\) is used in generalization bounds as an analogue to the class’s size in the finite case.
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(2017). Shattering Coefficient. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_759
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_759
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