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Boost Properties

The Boost type exposes the following members.

Public propertyCVFolds
If CVFolds greater than 1 then algorithms prunes the built decision tree using K-fold
Public propertyMaxCategories
Cluster possible values of a categorical variable into K less than or equals maxCategories clusters to find a suboptimal split
Public propertyMaxDepth
The maximum possible depth of the tree
Public propertyMinSampleCount
If the number of samples in a node is less than this parameter then the node will not be split
Public propertyPtr
Pointer to the unmanaged object
(Inherited from UnmanagedObject.)
Public propertyRegressionAccuracy
Termination criteria for regression trees
Public propertyTruncatePrunedTree
If true then pruned branches are physically removed from the tree
Public propertyUse1SERule
If true then a pruning will be harsher
Public propertyUseSurrogates
If true then surrogate splits will be built
See Also