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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.IteratedSingleClassifierEnhancer
weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
weka.classifiers.meta.RotationForest
public class RotationForest
Class for construction a Rotation Forest. Can do classification and regression depending on the base learner.
For more information, see
Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630. URL http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.211.
@article{Rodriguez2006, author = {Juan J. Rodriguez and Ludmila I. Kuncheva and Carlos J. Alonso}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, number = {10}, pages = {1619-1630}, title = {Rotation Forest: A new classifier ensemble method}, volume = {28}, year = {2006}, ISSN = {0162-8828}, URL = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.211} }Valid options are:
-N Whether minGroup (-G) and maxGroup (-H) refer to the number of groups or their size. (default: false)
-G <num> Minimum size of a group of attributes: if numberOfGroups is true, the minimum number of groups. (default: 3)
-H <num> Maximum size of a group of attributes: if numberOfGroups is true, the maximum number of groups. (default: 3)
-P <num> Percentage of instances to be removed. (default: 50)
-F <filter specification> Full class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.PrincipalComponents-R 1.0"
-S <num> Random number seed. (default 1)
-I <num> Number of iterations. (default 10)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
Constructor Summary | |
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RotationForest()
Constructor. |
Method Summary | |
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void |
buildClassifier(Instances data)
builds the classifier. |
double[] |
distributionForInstance(Instance instance)
Calculates the class membership probabilities for the given test instance. |
int |
getMaxGroup()
Gets the maximum size of a group. |
int |
getMinGroup()
Gets the minimum size of a group. |
boolean |
getNumberOfGroups()
Get whether minGroup and maxGroup refer to the number of groups or their size |
java.lang.String[] |
getOptions()
Gets the current settings of the Classifier. |
Filter |
getProjectionFilter()
Gets the filter used to project the data. |
int |
getRemovedPercentage()
Gets the percentage of instances to be removed |
java.lang.String |
getRevision()
Returns the revision string. |
TechnicalInformation |
getTechnicalInformation()
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. |
java.lang.String |
globalInfo()
Returns a string describing classifier |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
java.lang.String |
maxGroupTipText()
Returns the tip text for this property |
java.lang.String |
minGroupTipText()
Returns the tip text for this property |
java.lang.String |
numberOfGroupsTipText()
Returns the tip text for this property |
java.lang.String |
projectionFilterTipText()
Returns the tip text for this property |
java.lang.String |
removedPercentageTipText()
Returns the tip text for this property |
void |
setMaxGroup(int maxGroup)
Sets the maximum size of a group. |
void |
setMinGroup(int minGroup)
Sets the minimum size of a group. |
void |
setNumberOfGroups(boolean numberOfGroups)
Set whether minGroup and maxGroup refer to the number of groups or their size |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setProjectionFilter(Filter projectionFilter)
Sets the filter used to project the data. |
void |
setRemovedPercentage(int removedPercentage)
Sets the percentage of instance to be removed |
java.lang.String |
toString()
Returns description of the Rotation Forest classifier. |
Methods inherited from class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer |
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getSeed, seedTipText, setSeed |
Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer |
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getNumIterations, numIterationsTipText, setNumIterations |
Methods inherited from class weka.classifiers.SingleClassifierEnhancer |
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classifierTipText, getCapabilities, getClassifier, setClassifier |
Methods inherited from class weka.classifiers.Classifier |
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classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public RotationForest()
Method Detail |
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public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class RandomizableIteratedSingleClassifierEnhancer
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-N Whether minGroup (-G) and maxGroup (-H) refer to the number of groups or their size. (default: false)
-G <num> Minimum size of a group of attributes: if numberOfGroups is true, the minimum number of groups. (default: 3)
-H <num> Maximum size of a group of attributes: if numberOfGroups is true, the maximum number of groups. (default: 3)
-P <num> Percentage of instances to be removed. (default: 50)
-F <filter specification> Full class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.PrincipalComponents-R 1.0"
-S <num> Random number seed. (default 1)
-I <num> Number of iterations. (default 10)
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
setOptions
in interface OptionHandler
setOptions
in class RandomizableIteratedSingleClassifierEnhancer
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class RandomizableIteratedSingleClassifierEnhancer
public java.lang.String numberOfGroupsTipText()
public void setNumberOfGroups(boolean numberOfGroups)
numberOfGroups
- whether minGroup and maxGroup refer to the number
of groups or their sizepublic boolean getNumberOfGroups()
public java.lang.String minGroupTipText()
public void setMinGroup(int minGroup) throws java.lang.IllegalArgumentException
minGroup
- the minimum value.
of attributes.
java.lang.IllegalArgumentException
public int getMinGroup()
public java.lang.String maxGroupTipText()
public void setMaxGroup(int maxGroup) throws java.lang.IllegalArgumentException
maxGroup
- the maximum value.
of attributes.
java.lang.IllegalArgumentException
public int getMaxGroup()
public java.lang.String removedPercentageTipText()
public void setRemovedPercentage(int removedPercentage) throws java.lang.IllegalArgumentException
removedPercentage
- the percentage.
java.lang.IllegalArgumentException
public int getRemovedPercentage()
public java.lang.String projectionFilterTipText()
public void setProjectionFilter(Filter projectionFilter)
projectionFilter
- the filter.public Filter getProjectionFilter()
public java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
public void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier
in class IteratedSingleClassifierEnhancer
data
- the training data to be used for generating the
classifier.
java.lang.Exception
- if the classifier could not be built successfullypublic double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance
in class Classifier
instance
- the instance to be classified
java.lang.Exception
- if distribution can't be computed successfullypublic static void main(java.lang.String[] argv)
argv
- the options
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