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This was repeated to build a forest of 500 regression trees at maximum with a minimum node size of five.
The process continues until each node reaches a user-specified minimum node size and becomes a terminal node.
No minimum node size or depth was set, the fraction of data in the bag was set to 0.7 without replacement.
4. Repeat steps 2-3 until a minimum node size is reached (usually <5).
The number of the minimum node size n min was 1.
In our example we specified a two-sided alpha of 0.15 and a minimum node size of 60 observations.
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We used the default package parameters to control tree growth, including: minimum within-node deviance =0.01(d e v i a n c e r o o t ), minimum allowable node size = 10, and minimum observations to a candidate child node = 5.
A minimum terminal node size of 500 samples was selected to avoid too many splits, with few observations, that are difficult to explain.
Partitioning stops if a minimum child node size is not met, the null hypothesis cannot be rejected for any of the eligible exposure indicators at a pre-specified alpha level, or no further partitions remain.
The expression level is reflected in the node size.
After a preliminary analysis for optimisation, we kept the default settings of the package, that is, number of variables tried at each split m try = p/3, number of trees=500 and minimum node size=5.
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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