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Exact(4)
Results show how well the Apprentice architecture approximates the function in comparison with stand-alone MLPs.
The new approach approximates the function Λ by a linear function.
In this framework, the learner receives samples and must select from a certain class a hypothesis that approximates the function to be learned.
This method approximates the function for the target attribute by learning a decision tree from previous examples.
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In their method, they utilize a rough approximation model, which is an approximation model with low accuracy and without learning process to approximate the function values.
If the solution were a smooth function, one could carry out a Taylor expansion, which is a way of approximating the function by polynomials of increasingly higher degree.
Inequality (4.11) corresponds to the relative error in approximating the function by for the th iteration.
Inequality (4.14) corresponds to the absolute error in approximating the function by for the th iteration.
A table of optimum parameters has been obtained for approximating the function through different design schemes.
Finally, we present other ways for approximating the function (cos ^{2n}{ x}), (nin mathbb {N}).
An ANN can approximate the function of multiple inputs and outputs.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com