Description Usage Arguments Value
Finds the best splitting value and feature to split on
1 2 3 4 |
x |
feature data set |
y |
dependent outcome |
featureList |
|
sampleIndex |
a list containing two integer vecotrs 'averagingSampleIndex' and 'splittingSampleIndex' which specify which of the features is used for splitting and which is used for estimating the beta in the leaves |
nodesize |
a list containing 'splittingNodeSize' and 'averagingNodeSize' which specify the nodesizes for the splitting and the aceraging sets. |
splitrule |
= "variance", |
categoricalFeatureCols |
= list() |
A list of two outputs: "splitFeature" is the best feature to split in order to minimize the split loss, "splitValue" is its corresponding split value.
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