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Two of the key elements in a learning problem are:
a set of hypothesis $\mathcal H$, and a set of data samples $\mathcal S$. $\mathcal H$
Inside $\mathcal H$, we have a lot of hypotheses, for example, $\mathcal h$. Given some input, e.g., $x_1$ and $x_2$, we can produce some outputs, e.g., $h(x_1)$ and $h(x_2)$. $\mathcal S$
A sample $\mathcal S$ is a fair sample drawn from all the possible inputs $\mathcal X$, where $\mathcal X$ is called the input space. A dataset $\mathcal S$ can be used as a probe of the hypothesis set $\mathcal H$.
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wiki/learning-theory/vc-dimension/
Two of the key elements in a learning problem are:$\mathcal H$ , and a set of data samples $\mathcal S$ . $\mathcal H$ $\mathcal H$ , we have a lot of hypotheses, for example, $\mathcal h$ . Given some input, e.g., $x_1$ and $x_2$ , we can produce some outputs, e.g., $h(x_1)$ and $h(x_2)$ . $\mathcal S$ $\mathcal S$ is a fair sample drawn from all the possible inputs $\mathcal X$ , where $\mathcal X$ is called the input space. A dataset $\mathcal S$ can be used as a probe of the hypothesis set $\mathcal H$ .
a set of hypothesis
Inside
A sample
https://datumorphism.leima.is/wiki/learning-theory/vc-dimension/
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