When using the SAS Viya decisionTree.dtreeTrain CAS action, which parameter controls the minimum number of training observations required before a node will be split?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — the minUseInSearch= parameter is correct because it sets the minimum number of training observations a node must have before it can be split. If a node has fewer observations than that, you don't split it, which acts as pre-pruning during tree growth.
Full Explanation
The minUseInSearch= parameter is correct because, in the SAS Viya decisionTree.dtreeTrain CAS action, it specifies the minimum number of observations that a node must contain before it is considered for splitting during tree growth. Nodes with fewer observations than this threshold are not split, acting as a pre-pruning mechanism. The maxLevel= parameter is wrong because it controls the maximum tree depth, not the minimum number of observations required before a split. The leafSize= parameter is wrong because it is a PROC HPSPLIT option name; in the CAS action, the equivalent control for the minimum node size before splitting is minUseInSearch=. The pruneMethod= parameter is wrong because it controls the post-pruning algorithm, not the splitting threshold used during tree growth.