weka.classifiers.trees.j48Consolidated
public class C45ConsolidatedPruneableClassifierTree extends weka.classifiers.trees.j48.C45PruneableClassifierTree
Modifier and Type | Field and Description |
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private static long |
serialVersionUID
for serialization
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m_CF, m_cleanup, m_collapseTheTree, m_pruneTheTree, m_subtreeRaising
Constructor and Description |
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C45ConsolidatedPruneableClassifierTree(weka.classifiers.trees.j48.ModelSelection toSelectLocModel,
boolean pruneTree,
float cf,
boolean raiseTree,
boolean cleanup,
boolean collapseTree)
Constructor for pruneable consolidated tree structure.
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Modifier and Type | Method and Description |
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void |
buildClassifier(weka.core.Instances data,
weka.core.Instances[] samplesVector)
Method for building a pruneable classifier consolidated tree.
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void |
buildTree(weka.core.Instances data,
weka.core.Instances[] samplesVector,
boolean keepData)
Builds the consolidated tree structure.
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protected weka.classifiers.trees.j48.ClassifierTree |
getNewTree(weka.core.Instances data,
weka.core.Instances[] samplesVector)
Returns a newly created tree.
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buildClassifier, collapse, getCapabilities, getNewTree, getRevision, prune
private static final long serialVersionUID
public C45ConsolidatedPruneableClassifierTree(weka.classifiers.trees.j48.ModelSelection toSelectLocModel, boolean pruneTree, float cf, boolean raiseTree, boolean cleanup, boolean collapseTree) throws java.lang.Exception
toSelectLocModel
- selection method for local splitting modelpruneTree
- true if the tree is to be prunedcf
- the confidence factor for pruningraiseTree
- true if subtree raising has to be performedcleanup
- true if cleanup has to be donejava.lang.Exception
- if something goes wrongpublic void buildClassifier(weka.core.Instances data, weka.core.Instances[] samplesVector) throws java.lang.Exception
data
- the data for pruning the consolidated treesamplesVector
- the vector of samples for building the consolidated treejava.lang.Exception
- if something goes wrongprotected weka.classifiers.trees.j48.ClassifierTree getNewTree(weka.core.Instances data, weka.core.Instances[] samplesVector) throws java.lang.Exception
data
- the data to work withsamplesVector
- the vector of samples for building the consolidated treejava.lang.Exception
- if something goes wrongpublic void buildTree(weka.core.Instances data, weka.core.Instances[] samplesVector, boolean keepData) throws java.lang.Exception
data
- the data for pruning the consolidated treesamplesVector
- the vector of samples used for consolidationkeepData
- is training data to be kept?java.lang.Exception
- if something goes wrong