A B C D E G I L M N O P R S T W 

A

addChild(Splitter, ADTree) - Method in class weka.classifiers.trees.adtree.PredictionNode
Adds a child to this node.
addReference(Instance) - Method in class weka.classifiers.trees.adtree.ReferenceInstances
Adds one instance reference to the end of the set.
ADTree - Class in weka.classifiers.trees
Class for generating an alternating decision tree.
ADTree() - Constructor for class weka.classifiers.trees.ADTree
 
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the string describing the attributes the split depends on.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the string describing the attributes the split depends on.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the string describing the attributes the split depends on.

B

boost() - Method in class weka.classifiers.trees.ADTree
Performs a single boosting iteration, using two-class optimized method.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the index of the branch that an instance applies to.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the index of the branch that an instance applies to.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the index of the branch that an instance applies to.
buildClassifier(Instances) - Method in class weka.classifiers.trees.ADTree
Builds a classifier for a set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.LADTree
Builds a classifier for a set of instances.

C

children() - Method in class weka.classifiers.trees.adtree.PredictionNode
Enumerates the children of this node.
clone() - Method in class weka.classifiers.trees.ADTree
Creates a clone that is identical to the current tree, but is independent.
clone() - Method in class weka.classifiers.trees.adtree.PredictionNode
Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.Splitter
Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Clones this node.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the string describing the comparision the split depends on for a particular branch.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the string describing the comparision the split depends on for a particular branch.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the string describing the comparision the split depends on for a particular branch.

D

distributionForInstance(Instance) - Method in class weka.classifiers.trees.ADTree
Returns the class probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.LADTree
Returns the class probability distribution for an instance.
done() - Method in class weka.classifiers.trees.ADTree
Frees memory that is no longer needed for a final model - will no longer be able to increment the classifier after calling this.
done() - Method in class weka.classifiers.trees.LADTree
 

E

enumerateMeasures() - Method in class weka.classifiers.trees.ADTree
Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.trees.LADTree
Returns an enumeration of the additional measure names.
equalTo(Splitter) - Method in class weka.classifiers.trees.adtree.Splitter
Tests whether two splitters are equivalent.
equalTo(Splitter) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Tests whether two splitters are equivalent.
equalTo(Splitter) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Tests whether two splitters are equivalent.

G

getCapabilities() - Method in class weka.classifiers.trees.ADTree
Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.LADTree
Returns default capabilities of the classifier.
getChildForBranch(int) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the child for a branch of the split.
getChildForBranch(int) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the child for a branch of the split.
getChildForBranch(int) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the child for a branch of the split.
getChildren() - Method in class weka.classifiers.trees.adtree.PredictionNode
Gets the children of this node.
getMeasure(String) - Method in class weka.classifiers.trees.ADTree
Returns the value of the named measure.
getMeasure(String) - Method in class weka.classifiers.trees.LADTree
Returns the value of the named measure.
getNumOfBoostingIterations() - Method in class weka.classifiers.trees.ADTree
Gets the number of boosting iterations.
getNumOfBoostingIterations() - Method in class weka.classifiers.trees.LADTree
Gets the number of boosting iterations.
getNumOfBranches() - Method in class weka.classifiers.trees.adtree.Splitter
Gets the number of branches of the split.
getNumOfBranches() - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the number of branches of the split.
getNumOfBranches() - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the number of branches of the split.
getOptions() - Method in class weka.classifiers.trees.ADTree
Gets the current settings of ADTree.
getOptions() - Method in class weka.classifiers.trees.LADTree
Gets the current settings of ADTree.
getRevision() - Method in class weka.classifiers.trees.ADTree
Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.adtree.PredictionNode
Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.adtree.ReferenceInstances
Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.LADTree
Returns the revision string.
getSaveInstanceData() - Method in class weka.classifiers.trees.ADTree
Gets whether the tree is to save instance data.
getSearchPath() - Method in class weka.classifiers.trees.ADTree
Gets the method of searching the tree for a new insertion.
getTechnicalInformation() - Method in class weka.classifiers.trees.ADTree
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.LADTree
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getValue() - Method in class weka.classifiers.trees.adtree.PredictionNode
Gets the prediction value of the node.
globalInfo() - Method in class weka.classifiers.trees.ADTree
Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.LADTree
Returns a string describing classifier
graph() - Method in class weka.classifiers.trees.ADTree
Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.LADTree
Returns graph describing the tree.
graphType() - Method in class weka.classifiers.trees.ADTree
Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.LADTree
Returns the type of graph this classifier represents.

I

initClassifier(Instances) - Method in class weka.classifiers.trees.ADTree
Sets up the tree ready to be trained, using two-class optimized method.
initClassifier(Instances) - Method in class weka.classifiers.trees.LADTree
Sets up the tree ready to be trained.
instancesDownBranch(int, Instances) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the subset of instances that apply to a particluar branch of the split.
instancesDownBranch(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the subset of instances that apply to a particluar branch of the split.
instancesDownBranch(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the subset of instances that apply to a particluar branch of the split.

L

LADTree - Class in weka.classifiers.trees
Class for generating a multi-class alternating decision tree using the LogitBoost strategy.
LADTree() - Constructor for class weka.classifiers.trees.LADTree
 
legend() - Method in class weka.classifiers.trees.ADTree
Returns the legend of the tree, describing how results are to be interpreted.
legend() - Method in class weka.classifiers.trees.LADTree
Returns the legend of the tree, describing how results are to be interpreted.
listOptions() - Method in class weka.classifiers.trees.ADTree
Returns an enumeration describing the available options..
listOptions() - Method in class weka.classifiers.trees.LADTree
Returns an enumeration describing the available options.

M

main(String[]) - Static method in class weka.classifiers.trees.ADTree
Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.LADTree
Main method for testing this class.
measureExamplesCounted() - Method in class weka.classifiers.trees.LADTree
Returns the number of examples "counted".
measureExamplesProcessed() - Method in class weka.classifiers.trees.ADTree
Returns the number of examples "counted".
measureNodesExpanded() - Method in class weka.classifiers.trees.ADTree
Returns the number of nodes expanded.
measureNodesExpanded() - Method in class weka.classifiers.trees.LADTree
Returns the number of nodes expanded.
measureNumLeaves() - Method in class weka.classifiers.trees.ADTree
Calls measure function for leaf size - the number of prediction nodes.
measureNumLeaves() - Method in class weka.classifiers.trees.LADTree
Calls measure function for leaf size.
measureNumPredictionLeaves() - Method in class weka.classifiers.trees.ADTree
Calls measure function for prediction leaf size - the number of prediction nodes without children.
measureNumPredictionLeaves() - Method in class weka.classifiers.trees.LADTree
Calls measure function for leaf size.
measureTreeSize() - Method in class weka.classifiers.trees.ADTree
Calls measure function for tree size - the total number of nodes.
measureTreeSize() - Method in class weka.classifiers.trees.LADTree
Calls measure function for tree size.
merge(ADTree) - Method in class weka.classifiers.trees.ADTree
Merges two trees together.
merge(PredictionNode, ADTree) - Method in class weka.classifiers.trees.adtree.PredictionNode
Merges this node with another.
merge(LADTree) - Method in class weka.classifiers.trees.LADTree
Merges two trees together.

N

next(int) - Method in class weka.classifiers.trees.ADTree
Performs one iteration.
next(int) - Method in class weka.classifiers.trees.LADTree
 
nextSplitAddedOrder() - Method in class weka.classifiers.trees.ADTree
Returns the next number in the order that splitter nodes have been added to the tree, and records that a new splitter has been added.
numOfBoostingIterationsTipText() - Method in class weka.classifiers.trees.ADTree
 
numOfBoostingIterationsTipText() - Method in class weka.classifiers.trees.LADTree
 

O

orderAdded - Variable in class weka.classifiers.trees.adtree.Splitter
The number this node was in the order of nodes added to the tree

P

PredictionNode - Class in weka.classifiers.trees.adtree
Class representing a prediction node in an alternating tree.
PredictionNode(double) - Constructor for class weka.classifiers.trees.adtree.PredictionNode
Creates a new prediction node.
predictiveError(Instances) - Method in class weka.classifiers.trees.LADTree
 

R

ReferenceInstances - Class in weka.classifiers.trees.adtree
Simple class that extends the Instances class making it possible to create subsets of instances that reference their source set.
ReferenceInstances(Instances, int) - Constructor for class weka.classifiers.trees.adtree.ReferenceInstances
Creates an empty set of instances.

S

saveInstanceDataTipText() - Method in class weka.classifiers.trees.ADTree
 
SEARCHPATH_ALL - Static variable in class weka.classifiers.trees.ADTree
search mode: Expand all paths
SEARCHPATH_HEAVIEST - Static variable in class weka.classifiers.trees.ADTree
search mode: Expand the heaviest path
SEARCHPATH_RANDOM - Static variable in class weka.classifiers.trees.ADTree
search mode: Expand a random path
SEARCHPATH_ZPURE - Static variable in class weka.classifiers.trees.ADTree
search mode: Expand the best z-pure path
searchPathTipText() - Method in class weka.classifiers.trees.ADTree
 
setChildForBranch(int, PredictionNode) - Method in class weka.classifiers.trees.adtree.Splitter
Sets the child for a branch of the split.
setChildForBranch(int, PredictionNode) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Sets the child for a branch of the split.
setChildForBranch(int, PredictionNode) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Sets the child for a branch of the split.
setNumOfBoostingIterations(int) - Method in class weka.classifiers.trees.ADTree
Sets the number of boosting iterations.
setNumOfBoostingIterations(int) - Method in class weka.classifiers.trees.LADTree
Sets the number of boosting iterations.
setOptions(String[]) - Method in class weka.classifiers.trees.ADTree
Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.LADTree
Parses a given list of options.
setSaveInstanceData(boolean) - Method in class weka.classifiers.trees.ADTree
Sets whether the tree is to save instance data.
setSearchPath(SelectedTag) - Method in class weka.classifiers.trees.ADTree
Sets the method of searching the tree for a new insertion.
setValue(double) - Method in class weka.classifiers.trees.adtree.PredictionNode
Sets the prediction value of the node.
Splitter - Class in weka.classifiers.trees.adtree
Abstract class representing a splitter node in an alternating tree.
Splitter() - Constructor for class weka.classifiers.trees.adtree.Splitter
 

T

TAGS_SEARCHPATH - Static variable in class weka.classifiers.trees.ADTree
The search modes
toString() - Method in class weka.classifiers.trees.ADTree
Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.LADTree
Returns a description of the classifier.
TwoWayNominalSplit - Class in weka.classifiers.trees.adtree
Class representing a two-way split on a nominal attribute, of the form: either 'is some_value' or 'is not some_value'.
TwoWayNominalSplit(int, int) - Constructor for class weka.classifiers.trees.adtree.TwoWayNominalSplit
Creates a new two-way nominal splitter.
TwoWayNumericSplit - Class in weka.classifiers.trees.adtree
Class representing a two-way split on a numeric attribute, of the form: either 'is < some_value' or 'is >= some_value'.
TwoWayNumericSplit(int, double) - Constructor for class weka.classifiers.trees.adtree.TwoWayNumericSplit
Creates a new two-way numeric splitter.

W

weka.classifiers.trees - package weka.classifiers.trees
 
weka.classifiers.trees.adtree - package weka.classifiers.trees.adtree
 
A B C D E G I L M N O P R S T W