The Forest_Drive function uses a training data set to generate a predictive model. You can input the model to the Forest_Predict function, which uses it to make predictions.
The size of each
individual decision tree generated by the Forest_Drive function must be less than 32 MB.
The factors that affect the size of a decision tree are the depth of the tree, the
number of categorical inputs, the number of numerical inputs, and the number of
surrogates. If the size of a decision tree exceeds 32 MB, the function issues an error
message. Therefore, control the factors in the input data that increase the size of
decision trees.
Aster Analytics provides a tree_size_estimator function that you can use to estimate maximum values for the arguments TreeSize and NumTrees, based on the cluster configuration and the number of predictor variables. The syntax is:
SELECT * FROM tree_size_estimator (ON inputtable NumericInputs ('predictor' [,…]));
The query results includes a row_count column. The average value of this column is the recommended maximum value for the argument NumTrees.