- OutputTable
- Specify the name for the output table that is to contain the final decision tree (the model table). The output_table must not exceed 64 characters.
- FinalResponseTable
- [Optional] Specify the name for the output table that is to contain the final PID and response pair from the response table and the node_id from the final single drive tree.
- IntermediateSplitsTable
- [Disallowed with SplitsTable, optional otherwise.] Specify the name for the intermediate splits table, if it is to be saved.
- AttributeNameColumns
- Specify the names of the InputTable or AttributeTable columns that have the attribute names.
- AttributeValueColumn
- Specify the name of the InputTable or AttributeTable columns that have the attribute values.
- ResponseColumn
- Specify the name of the ResponseTable column that contains the response variable.
- IDColumns
- Specify the names of the ResponseTable and AttributeTable columns that specify the ID of the instance.
- CategoricalEncoding
- [Optional with CategoricalAttributeTable, disallowed otherwise.] Specify algorithm for encoding categorical columns:
Option Description GrayCode Recommended when accuracy is critical. Depending on available memory, out-of-memory errors can occur if a categorical column has more than about 20 unique levels, even with a small data set. Hashing Optimizes calculation speed and minimizes memory use, possibly decreasing accuracy. - SplitsValueColumn
- [Optional] If you specify SplitsTable, this syntax element specifies the name of the column that contains the split value.
- ApproxSplits
- [Optional] Specify whether to use approximate percentiles (true) or exact percentiles (false). Internally, the function uses percentile values as split values.
- NumSplits
- [Optional] Specify the number of splits to consider for each variable. The num_splits_to_consider must be an INTEGER. If ApproxSplits is true, num_splits_to_consider must be greater than 1; otherwise, it must be greater than 0. The function does not consider all possible splits for all attributes.
- MinNodeSize
- [Optional] Specify the decision tree stopping criterion and the minimum size of any particular node within each decision tree.
- MaxDepth
- Specify a decision tree stopping criterion. If the tree reaches a depth past this value, the algorithm stops looking for splits. Decision trees can grow up to (2(max_depth+1) - 1) nodes. This stopping criteria has the greatest effect on function performance.
- Weighted
- [Optional] Specify whether to build a weighted decision tree. If you specify 'true', you must also specify the WeightColumn syntax element.
- WeightColumn
- [Required with Weighted, otherwise optional.] Specify the name of the response table column that contains the weights of the attribute values.
- SplitMeasure
- [Optional] Specify the impurity measurement to use while constructing the decision tree. If the tree is weighted, this value cannot be 'chisquare'.
- OutputProb
- [Optional] Specify whether to output the probability distributions for each node.
- ResponseProbDistType
- [Optional] Specifies the probability distribution type.