- AttributeTable
- Specifies the name of the table that contains the attributes and values of the data.
- AttributeNameColumns
- Specifies the names of attribute table columns that contain the data attributes.
- AttributeValueColumns
- Specifies the names of attribute table columns that contain the data values.
- CategoricalAttributeTable
- [Optional] Specifies the name of the table that contains the names of the categorical attributes.
- ResponseTable
- Specifies the name of the table that contains the responses (labels) of the data.
- OutputTable
- Specifies the name of the output table where the function stores the predictive model it generates.
- IDColumns
- Specifies the names of the columns in the response and attribute tables that specify the identifier of the instance.
- ResponseColumn
- Specifies the name of the response table column that contains the responses (labels) of the data.
- IterNum
- [Optional] Specifies the number of iterations to boost the weak classifiers, which is also the number of weak classifiers in the ensemble (T). The iterations must be an INTEGER in the range [2, 200]. Default: 20.
- NumSplits
- [Optional] Specifies the number of splits to try for each attribute in the node splitting. The splits must be an INTEGER. Default: 10.
- ApproxSplits
- [Optional] Specifies whether to use approximate percentiles. Default: 'true'.
- SplitMeasure
- [Optional] Specifies the type of measure to use in node splitting. Default: 'gini'.
- MaxDepth
- [Optional] Specifies the depth of each weak classifier. The max_depth must be an INTEGER in the range [1, 10]. Default: 3.MaxDepth does not control the depth of the final tree, as MaxDepth in Single_Tree_Drive does.
- MinNodeSize
- [Optional] Specifies the minimum size of any node within each decision tree. The min_node_size must be an INTEGER. Default: 100.
- DropOutputTable
- [Optional] Specifies whether to drop output_table if it exists. Default: 'false'.
- OutputResponseProbDist
- [Optional] Specifies whether to output probabilities. Default: 'false'. If you specify 'true', the function outputs the
probability distributions for each node in the output table.Set this argument to 'true' if you intend to set OutputResponseProbDist to 'true' for the AdaBoost_Predict function.