The Single_Tree_Drive function creates a single decision tree in a distributed fashion, either weighted or unweighted. The model table that this function outputs can be input to the function Single_Tree_Predict.
Single_Tree_Drive requires vworkers to communicate with each other during the tree-building process. This communication can be very expensive, depending on the number of variables and the number of possible splits; therefore, the algorithm uses a sampling approach to reduce the number of splits.
The Single_Tree_Drive function uses the functions Approximate Percentile and Percentile to sample the split values. The split table has all the splits for all the numerical attributes that were considered in building the tree.