Decision tree model for classification or regression.
Represents a gradient boosted trees model.
Represents a gradient boosted trees model.
:: DeveloperApi :: Information gain statistics for each split
:: DeveloperApi :: Information gain statistics for each split
:: DeveloperApi :: Node in a decision tree.
:: DeveloperApi :: Node in a decision tree.
About node indexing: Nodes are indexed from 1. Node 1 is the root; nodes 2, 3 are the left, right children. Node index 0 is not used.
:: DeveloperApi :: Predicted value for a node
:: DeveloperApi :: Predicted value for a node
Represents a random forest model.
Represents a random forest model.
:: DeveloperApi :: Split applied to a feature
:: DeveloperApi :: Split applied to a feature
feature index
Threshold for continuous feature. Split left if feature is less than or equal to threshold, else right.
type of feature -- categorical or continuous
Split left if categorical feature value is in this set, else right.
Decision tree model for classification or regression. This model stores the decision tree structure and parameters.