public class FTInnerNode extends FTtree
Constructor and Description |
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FTInnerNode(boolean errorOnProbabilities,
int numBoostingIterations,
int minNumInstances,
double weightTrimBeta,
boolean useAIC)
Constructor for Functional Inner tree node.
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Modifier and Type | Method and Description |
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void |
buildClassifier(Instances data)
Method for building a Functional Inner tree (only called for the root node).
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void |
buildTree(Instances data,
SimpleLinearRegression[][] higherRegressions,
double totalInstanceWeight,
double higherNumParameters)
Method for building the tree structure.
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double[] |
distributionForInstance(Instance instance)
Returns the class probabilities for an instance given by the Functional tree.
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String |
getRevision()
Returns the revision string.
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double |
prune()
Prunes a tree using C4.5 pruning procedure.
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assignIDs, assignLeafModelNumbers, cleanup, getConstError, getModelParameters, getNodes, getNodes, getNumInnerNodes, getNumLeaves, graph, hasModels, modelDistributionForInstance, modelsToString, numLeaves, numNodes, toString
getMaxIterations, getNumRegressions, getUseAIC, getUsedAttributes, getWeightTrimBeta, percentAttributesUsed, setHeuristicStop, setMaxIterations, setUseAIC, setWeightTrimBeta
classifyInstance, debugTipText, forName, getCapabilities, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions
public FTInnerNode(boolean errorOnProbabilities, int numBoostingIterations, int minNumInstances, double weightTrimBeta, boolean useAIC)
errorOnProbabilities
- Use error on probabilities for stopping criterion of LogitBoost?numBoostingIterations
- sets the numBoostingIterations parameterminNumInstances
- minimum number of instances at which a node is considered for splittingpublic void buildClassifier(Instances data) throws Exception
buildClassifier
in class FTtree
data
- the data to train withException
- if something goes wrongpublic void buildTree(Instances data, SimpleLinearRegression[][] higherRegressions, double totalInstanceWeight, double higherNumParameters) throws Exception
buildTree
in class FTtree
data
- the training data passed on to this nodehigherRegressions
- An array of regression functions produced by LogitBoost at higher
levels in the tree. They represent a logistic regression model that is refined locally
at this node.totalInstanceWeight
- the total number of training exampleshigherNumParameters
- effective number of parameters in the logistic regression model built
in parent nodesException
- if something goes wrongpublic double prune() throws Exception
public double[] distributionForInstance(Instance instance) throws Exception
distributionForInstance
in class FTtree
instance
- the instanceException
- if distribution can't be computed successfullypublic String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class FTtree
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