Uses of Package
gov.sandia.cognition.learning.algorithm.tree

Packages that use gov.sandia.cognition.learning.algorithm.tree

Package	Description
gov.sandia.cognition.learning.algorithm.tree	Provides decision tree learning algorithms.

Classes in gov.sandia.cognition.learning.algorithm.tree used by gov.sandia.cognition.learning.algorithm.tree

Class and Description
AbstractDecisionTreeLearner The AbstractDecisionTreeLearner implements common functionality for learning algorithms that learn a decision tree.
AbstractDecisionTreeNode The AbstractDecisionTreeNode class implements common functionality for a decision tree node.
AbstractVectorThresholdMaximumGainLearner An abstract class for decider learners that produce a threshold function on a vector element based on maximizing some gain value.
CategorizationTree The CategorizationTree class extends the DecisionTree class to implement a decision tree that does categorization.
CategorizationTreeLearner The CategorizationTreeLearner class implements a supervised learning algorithm for learning a categorization tree.
CategorizationTreeNode The CategorizationTreeNode implements a DecisionTreeNode for a tree that does categorization.
DeciderLearner The DeciderLearner interface defines the functionality of a learner that can be used to learn a decision function inside a decision tree.
DecisionTree The DecisionTree class implements a standard decision tree that is made up of DecisionTreeNode objects.
DecisionTreeNode The DecisionTreeNode interface defines the functionality of a node in a decision tree.
PriorWeightedNodeLearner The PriorWeightedNodeLearner interface specifies the ability to configure prior weights on the learning algorithm that searches for a decision function inside a decision tree.
RandomSubVectorThresholdLearner Learns a decision function by taking a randomly sampling a subspace from a given set of input vectors and then learning a threshold function by passing the subspace vectors to a sublearner.
RegressionTree The RegressionTree class extends the DecisionTree class to implement a decision tree that does regression.
RegressionTreeLearner The RegressionTreeLearner class implements a learning algorithm for a regression tree that makes use of a decider learner and a regression learner.
RegressionTreeNode The RegressionTreeNode implements a DecisionTreeNode for a tree that does regression.
VectorThresholdGiniImpurityLearner Learns vector thresholds based on the Gini impurity measure.
VectorThresholdHellingerDistanceLearner A categorization tree decision function learner on vector data that learns a vector value threshold function using the Hellinger distance.
VectorThresholdInformationGainLearner The VectorThresholdInformationGainLearner computes the best threshold over a dataset of vectors using information gain to determine the optimal index and threshold.
VectorThresholdLearner An interface class for decider learners that produce a threshold function on a vector element based on maximizing some gain value.