model

Type Members

1. class DecisionTreeModel extends Serializable

   

   :: Experimental :: Decision tree model for classification or regression.

   :: Experimental :: Decision tree model for classification or regression. This model stores the decision tree structure and parameters.

   Annotations

   @Experimental()

2. class GradientBoostedTreesModel extends TreeEnsembleModel

   

   :: Experimental :: Represents a gradient boosted trees model.

   :: Experimental :: Represents a gradient boosted trees model.

   Annotations

   @Experimental()

3. class InformationGainStats extends Serializable

   

   :: DeveloperApi :: Information gain statistics for each split

   :: DeveloperApi :: Information gain statistics for each split

   Annotations

   @DeveloperApi()

4. class Node extends Serializable with Logging

   

   :: 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.

   Annotations

   @DeveloperApi()

5. class Predict extends Serializable

   

   Predicted value for a node

   Predicted value for a node

   Annotations

   @DeveloperApi()

6. class RandomForestModel extends TreeEnsembleModel

   

   :: Experimental :: Represents a random forest model.

   :: Experimental :: Represents a random forest model.

   Annotations

   @Experimental()

7. case class Split(feature: Int, threshold: Double, featureType: FeatureType, categories: List[Double]) extends Product with Serializable

   

   :: DeveloperApi :: Split applied to a feature

   :: DeveloperApi :: Split applied to a feature

   feature

   feature index

   threshold

   Threshold for continuous feature. Split left if feature <= threshold, else right.

   featureType

   type of feature -- categorical or continuous

   categories

   Split left if categorical feature value is in this set, else right.

   Annotations

   @DeveloperApi()