ClusteringTreeModel
Related Docs:
object ClusteringTreeModel
| package cluster
Return an iterator over the nodes of the decision tree
Return an iterator over the nodes of the decision tree
an iterator over the tree nodes, in breadth first order
Evaluate a feature vector against a decision tree and return the id of the leaf node it "landed" at
Evaluate a feature vector against a decision tree and return the id of the leaf node it "landed" at
The feature vector to evaluate
The id of the decision tree leaf node the feature vector reached
Traverse a Spark decision tree and convert each path from root to a leaf into a "rule" that is a sequence of individual predicates representing the decision made at each internal node.
Traverse a Spark decision tree and convert each path from root to a leaf into a "rule" that is a sequence of individual predicates representing the decision made at each internal node.
a partial function that returns name of a feature given its index
a partial function from feature index to number of categories. If an index is not present then it is assumed to be numeric
a map from leaf-node prediction values to a collection of all rules that will yield that value.
Enhance a Spark DecisionTreeModel object with methods for Random Forest clustering