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They can be analyzed much more easily than other models, especially when additional regulatory complexity is present and this becomes more pronounced as the model size increases.
On the other hand, the requirement that shared haplotypes must traverse the same path through the model to be declared IBD becomes more onerous as the model size increases, and detection rates can drop.
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Therefore, we allowed the selection of a larger model if the criterion function gives a better result and the model's size increases by an amount smaller than the threshold δ.
This is because the value of T does not change the model size while increasing it introduces more information for decision making.
It can be observed that with increasing model size the number of different trees increases to 187 for models with 16 internal nodes, while many of these models only differ by minor important splits at the bottom of the trees, which do not contribute much to the reduction of impurity and are medically very similar.
The use of iterative linear algebra Methods, will be useful in solving for steady states of PBN models when the size increases.
Apparently, CPU times decrease with a smaller number of demand elements due to the decrease in model size and they increase with a higher capacity load.
This technique has an advantage in that the model size does not increase with the number of DTs as is the case with ensemble methods such as bagging [9, 10].
Furthermore, because the ERM approach cannot control the complexity of the regression model, increasing the window size increases the VC-dimension of the prediction model.
Both AIC and BIC become more likely to select the correct model as the sample size increases (data not shown).
Higher order terms significantly increase the model size, yet yield litter gain in denoising results.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com