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Use model selection methods when comparing complexity classes with different number of parameters #6

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pberkes opened this issue Mar 5, 2017 · 0 comments
Open

Use model selection methods when comparing complexity classes with different number of parameters #6

pberkes opened this issue Mar 5, 2017 · 0 comments

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@pberkes
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pberkes commented Mar 5, 2017

Complexity classes with more parameters will always fit the data better.

Use cross-validation methods, or just an AIC correction, to take that into account.
@pberkes pberkes changed the title Use model selection methods when comparing complexity classes with different number of paramters Use model selection methods when comparing complexity classes with different number of parameters Mar 5, 2017
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@pberkes