Uses of Class
marytts.cart.Node

Packages that use Node

marytts.cart
marytts.cart.io

Uses of Node in marytts.cart

Classes in marytts.cart with type parameters of type Node

class

NodeIterator<T extends Node>

Subclasses of Node in marytts.cart

class	DecisionNode A decision node that determines the next Node to go to in the CART.
static class	DecisionNode.BinaryByteDecisionNode A binary decision Node that compares two byte values.
static class	DecisionNode.BinaryFloatDecisionNode A binary decision Node that compares two float values.
static class	DecisionNode.BinaryShortDecisionNode A binary decision Node that compares two short values.
static class	DecisionNode.ByteDecisionNode An decision Node with an arbitrary number of daughters.
static class	DecisionNode.ShortDecisionNode An decision Node with an arbitrary number of daughters.
class	DirectedGraphNode A type of node that can be at the same time a decision node and a leaf node, and that can have more than one mother.
class	LeafNode The leaf of a CART.
static class	LeafNode.FeatureVectorLeafNode
static class	LeafNode.FloatLeafNode A leaf class that is suitable for regression trees.
static class	LeafNode.IntAndFloatArrayLeafNode
static class	LeafNode.IntArrayLeafNode An LeafNode class suitable for representing the leaves of classification trees -- the leaf is a collection of items identified by an index number.
static class	LeafNode.PdfLeafNode A leaf class that is suitable for regression trees.
static class	LeafNode.StringAndFloatLeafNode

Fields in marytts.cart declared as Node

protected Node[]	DecisionNode.daughters
protected Node	Node.mother
protected Node	DirectedGraph.rootNode

Methods in marytts.cart that return Node

Node	DecisionNode.getDaughter(int index) Get the daughter at the specified index
Node	DirectedGraphNode.getLeafNode()
Node	Node.getMother() Get the mother node of this node
Node	DirectedGraphNode.getMother() Get a mother node of this node.
Node	DirectedGraphNode.getNextNode(FeatureVector fv)
abstract Node	DecisionNode.getNextNode(FeatureVector featureVector) Select a daughter node according to the value in the given target
Node	DecisionNode.BinaryByteDecisionNode.getNextNode(FeatureVector featureVector) Select a daughter node according to the value in the given target
Node	DecisionNode.BinaryShortDecisionNode.getNextNode(FeatureVector featureVector) Select a daughter node according to the value in the given target
Node	DecisionNode.BinaryFloatDecisionNode.getNextNode(FeatureVector featureVector) Select a daughter node according to the value in the given target
Node	DecisionNode.ByteDecisionNode.getNextNode(FeatureVector featureVector) Select a daughter node according to the value in the given target
Node	DecisionNode.ShortDecisionNode.getNextNode(FeatureVector featureVector) Select a daughter node according to the value in the given target
Node	Node.getRootNode()
Node	DirectedGraph.getRootNode() Get the root node of this CART
Node	StringPredictionTree.interpretToNode(FeatureVector featureVector, int minNumberOfData) TODO: copied from CART, does not work as expected with minNumberOfData = 0 Passes the given item through this CART and returns the leaf Node, or the Node it stopped walking down.
Node	CART.interpretToNode(FeatureVector featureVector, int minNumberOfData) Passes the given item through this CART and returns the leaf Node, or the Node it stopped walking down.
Node	CART.interpretToNode(Target target, int minNumberOfData) Passes the given item through this CART and returns the leaf Node, or the Node it stopped walking down.
static Node	CART.replaceLeafByCart(CART cart, LeafNode leaf) In this tree, replace the given leaf with the given CART

Methods in marytts.cart that return types with arguments of type Node

java.util.List<Node>	DirectedGraphNode.getMothers()
java.util.Iterator<Node>	DirectedGraph.getNodeIterator() Return an iterator which returns all nodes in the tree exactly once.
java.lang.Iterable<Node>	DirectedGraph.getNodes() A representation of the corresponding node iterator that can be used in extended for() statements.

Methods in marytts.cart with parameters of type Node

void	DecisionNode.addDaughter(Node daughter) Add a daughter to the node
int	DirectedGraphNode.getNodeIndex(Node aMother) Return this node's index in the given mother's array of daughters.
protected java.lang.Object	DirectedGraph.interpret(Node n, FeatureVector fv) Follow the directed graph down to the most specific leaf with data, starting from node n.
void	DirectedGraphNode.removeMother(Node aMother) Remove the given node from the list of mothers.
void	DecisionNode.replaceDaughter(Node newDaughter, int index) Replace daughter at given index with another daughter
void	DirectedGraphNode.setLeafNode(Node newNode)
void	Node.setMother(Node node, int nodeIndex) set the mother node of this node, and remember this node's index in mother.
void	DirectedGraphNode.setMother(Node node, int nodeIndex)
void	DirectedGraph.setRootNode(Node rNode) Set the root node of this CART

Constructors in marytts.cart with parameters of type Node

CART(Node rootNode, FeatureDefinition featDef)
Build a new cart with the given node as the root node

CART(Node rootNode, FeatureDefinition featDef, java.util.Properties properties)
Build a new cart with the given node as the root node

DirectedGraph(Node rootNode, FeatureDefinition featDef)
Build a new graph with the given node as the root node

DirectedGraph(Node rootNode, FeatureDefinition featDef, java.util.Properties properties)
Build a new graph with the given node as the root node

DirectedGraphNode(DecisionNode decisionNode, Node leafNode)

NodeIterator(Node rootNode, boolean showLeafNodes, boolean showDecisionNodes, boolean showDirectedGraphNodes)
Iterate over the subtree below rootNode.

StringPredictionTree(Node aRootNode, FeatureDefinition aFeatDef, java.lang.String[] aTargetDecoding)

Uses of Node in marytts.cart.io

Methods in marytts.cart.io that return Node

Node	WagonCARTReader.load(java.io.BufferedReader reader, FeatureDefinition featDefinition) This loads a cart from a wagon tree in textual format, from a reader.
Node	WagonCARTReader.load(java.lang.String fileName, FeatureDefinition featDefinition, java.lang.String[] dummy) Load the cart from the given file

Methods in marytts.cart.io with parameters of type Node

void	WagonCARTReader.fillLeafs(Node root, FeatureVector[] featureVectors) Fill the FeatureVector leafs of a tree with the given feature vectors.