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DecisionTreeLearningBase Properties

The DecisionTreeLearningBase type exposes the following members.

Public propertyAttributes
Gets or sets the collection of attributes to be processed by the induced decision tree.
Protected propertyAttributeUsageCount
Gets how many times each attribute has already been used in the current path. In the original C4.5 and ID3 algorithms, attributes could be re-used only once, but in the framework implementation this behaviour can be adjusted by setting the Join property.
Public propertyJoin
Gets or sets how many times one single variable can be integrated into the decision process. In the original ID3 algorithm, a variable can join only one time per decision path (path from the root to a leaf). If set to zero, a single variable can participate as many times as needed. Default is 1.
Public propertyMaxHeight
Gets or sets the maximum allowed height when learning a tree. If set to zero, the tree can have an arbitrary length. Default is 0.
Public propertyMaxVariables
Gets or sets the maximum number of variables that can enter the tree. A value of zero indicates there is no limit. Default is 0 (there is no limit on the number of variables).
Public propertyModel
Gets or sets the decision trees being learned.
Public propertyParallelOptions
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.)
Public propertyToken
Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.)
See Also