Uses of Package
com.imsl.datamining.decisionTree

Packages that use com.imsl.datamining.decisionTree

Package	Description
com.imsl.datamining.decisionTree	Decision trees.

Classes in com.imsl.datamining.decisionTree used by com.imsl.datamining.decisionTree

Class and Description
ALACART Generates a decision tree using the CARTTM method of Breiman, Friedman, Olshen and Stone (1984).
C45 Generates a decision tree using the C4.5 algorithm for a categorical response variable and categorical or quantitative predictor variables.
CHAID Generates a decision tree using CHAID for categorical or discrete ordered predictor variables.
DecisionTree Abstract class for generating a decision tree for a single response variable and one or more predictor variables.
DecisionTree.MaxTreeSizeExceededException Exception thrown when the maximum tree size has been exceeded.
DecisionTree.PruningFailedToConvergeException Exception thrown when pruning fails to converge.
DecisionTree.PureNodeException Exception thrown when attempting to split a node that is already pure (response variable is constant).
DecisionTreeInfoGain Abstract class that extends DecisionTree for classes that use an information gain criteria.
DecisionTreeInfoGain.GainCriteria Specifies which information gain criteria to use in determining the best split at each node.
DecisionTreeSurrogateMethod Methods to account for missing values in predictor variables.
QUEST Generates a decision tree using the QUEST algorithm for a categorical response variable and categorical or quantitative predictor variables.
RandomTrees Generates predictions using a random forest of decision trees.
Tree Serves as the root node of a decision tree and contains information about the relationship of child nodes.
TreeNode A DecisionTree node that is a child node of Tree.