Interface | Description |
---|---|
DecisionTreeSurrogateMethod |
Methods to account for missing values in predictor variables.
|
Class | Description |
---|---|
ALACART |
Generates a decision tree using the CARTTM method of Breiman,
Friedman, Olshen and Stone (1984).
|
C45 |
Generates a decision tree using the C4.5 algorithm for a categorical response
variable and categorical or quantitative predictor variables.
|
CHAID |
Generates a decision tree using CHAID for categorical or discrete ordered
predictor variables.
|
DecisionTree |
Abstract class for generating a decision tree for a single response variable
and one or more predictor variables.
|
DecisionTreeInfoGain |
Abstract class that extends
DecisionTree for classes that use an
information gain criteria. |
DecisionTreeInfoGain.GainCriteria |
Specifies which information gain criteria to use in determining the best
split at each node.
|
QUEST |
Generates a decision tree using the QUEST algorithm for a categorical
response variable and categorical or quantitative predictor variables.
|
RandomTrees |
Generates predictions using a random forest of decision trees.
|
Tree |
Serves as the root node of a decision tree and contains information about the
relationship of child nodes.
|
TreeNode |
A
DecisionTree node that is a child node of Tree . |
Exception | Description |
---|---|
DecisionTree.MaxTreeSizeExceededException |
Exception thrown when the maximum tree size has been exceeded.
|
DecisionTree.PruningFailedToConvergeException |
Exception thrown when pruning fails to converge.
|
DecisionTree.PureNodeException |
Exception thrown when attempting to split a node that is already pure
(response variable is constant).
|
RandomTrees.ReflectiveOperationException |
Class that wraps exceptions thrown by reflective operations in core
reflection.
|
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Built May 19 2016.