Package weka.classifiers.meta
Class MultiScheme
- java.lang.Object
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- weka.classifiers.Classifier
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- weka.classifiers.MultipleClassifiersCombiner
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- weka.classifiers.RandomizableMultipleClassifiersCombiner
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- weka.classifiers.meta.MultiScheme
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- All Implemented Interfaces:
java.io.Serializable
,java.lang.Cloneable
,CapabilitiesHandler
,OptionHandler
,Randomizable
,RevisionHandler
public class MultiScheme extends RandomizableMultipleClassifiersCombiner
Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data. Performance is measured based on percent correct (classification) or mean-squared error (regression). Valid options are:-X <number of folds> Use cross validation for model selection using the given number of folds. (default 0, is to use training error)
-S <num> Random number seed. (default 1)
-B <classifier specification> Full class name of classifier to include, followed by scheme options. May be specified multiple times. (default: "weka.classifiers.rules.ZeroR")
-D If set, classifier is run in debug mode and may output additional info to the console
- Version:
- $Revision: 1.25 $
- Author:
- Len Trigg (trigg@cs.waikato.ac.nz)
- See Also:
- Serialized Form
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Constructor Summary
Constructors Constructor Description MultiScheme()
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description void
buildClassifier(Instances data)
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.java.lang.String
classifiersTipText()
Returns the tip text for this propertyjava.lang.String
debugTipText()
Returns the tip text for this propertydouble[]
distributionForInstance(Instance instance)
Returns class probabilities.int
getBestClassifierIndex()
Get the index of the classifier that was determined as best during cross-validation.Classifier
getClassifier(int index)
Gets a single classifier from the set of available classifiers.Classifier[]
getClassifiers()
Gets the list of possible classifers to choose from.boolean
getDebug()
Get whether debugging is turned onint
getNumFolds()
Gets the number of folds for cross-validation.java.lang.String[]
getOptions()
Gets the current settings of the Classifier.java.lang.String
getRevision()
Returns the revision string.int
getSeed()
Gets the random number seed.java.lang.String
globalInfo()
Returns a string describing classifierjava.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
numFoldsTipText()
Returns the tip text for this propertyjava.lang.String
seedTipText()
Returns the tip text for this propertyvoid
setClassifiers(Classifier[] classifiers)
Sets the list of possible classifers to choose from.void
setDebug(boolean debug)
Set debugging modevoid
setNumFolds(int numFolds)
Sets the number of folds for cross-validation.void
setOptions(java.lang.String[] options)
Parses a given list of options.void
setSeed(int seed)
Sets the seed for random number generation.java.lang.String
toString()
Output a representation of this classifier-
Methods inherited from class weka.classifiers.MultipleClassifiersCombiner
getCapabilities
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Methods inherited from class weka.classifiers.Classifier
classifyInstance, forName, makeCopies, makeCopy
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Method Detail
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globalInfo
public java.lang.String globalInfo()
Returns a string describing classifier- Returns:
- a description suitable for displaying in the explorer/experimenter gui
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listOptions
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classRandomizableMultipleClassifiersCombiner
- Returns:
- an enumeration of all the available options.
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setOptions
public void setOptions(java.lang.String[] options) throws java.lang.Exception
Parses a given list of options. Valid options are:-X <number of folds> Use cross validation for model selection using the given number of folds. (default 0, is to use training error)
-S <num> Random number seed. (default 1)
-B <classifier specification> Full class name of classifier to include, followed by scheme options. May be specified multiple times. (default: "weka.classifiers.rules.ZeroR")
-D If set, classifier is run in debug mode and may output additional info to the console
- Specified by:
setOptions
in interfaceOptionHandler
- Overrides:
setOptions
in classRandomizableMultipleClassifiersCombiner
- Parameters:
options
- the list of options as an array of strings- Throws:
java.lang.Exception
- if an option is not supported
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getOptions
public java.lang.String[] getOptions()
Gets the current settings of the Classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classRandomizableMultipleClassifiersCombiner
- Returns:
- an array of strings suitable for passing to setOptions
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classifiersTipText
public java.lang.String classifiersTipText()
Returns the tip text for this property- Overrides:
classifiersTipText
in classMultipleClassifiersCombiner
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setClassifiers
public void setClassifiers(Classifier[] classifiers)
Sets the list of possible classifers to choose from.- Overrides:
setClassifiers
in classMultipleClassifiersCombiner
- Parameters:
classifiers
- an array of classifiers with all options set.
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getClassifiers
public Classifier[] getClassifiers()
Gets the list of possible classifers to choose from.- Overrides:
getClassifiers
in classMultipleClassifiersCombiner
- Returns:
- the array of Classifiers
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getClassifier
public Classifier getClassifier(int index)
Gets a single classifier from the set of available classifiers.- Overrides:
getClassifier
in classMultipleClassifiersCombiner
- Parameters:
index
- the index of the classifier wanted- Returns:
- the Classifier
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seedTipText
public java.lang.String seedTipText()
Returns the tip text for this property- Overrides:
seedTipText
in classRandomizableMultipleClassifiersCombiner
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setSeed
public void setSeed(int seed)
Sets the seed for random number generation.- Specified by:
setSeed
in interfaceRandomizable
- Overrides:
setSeed
in classRandomizableMultipleClassifiersCombiner
- Parameters:
seed
- the random number seed
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getSeed
public int getSeed()
Gets the random number seed.- Specified by:
getSeed
in interfaceRandomizable
- Overrides:
getSeed
in classRandomizableMultipleClassifiersCombiner
- Returns:
- the random number seed
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numFoldsTipText
public java.lang.String numFoldsTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getNumFolds
public int getNumFolds()
Gets the number of folds for cross-validation. A number less than 2 specifies using training error rather than cross-validation.- Returns:
- the number of folds for cross-validation
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setNumFolds
public void setNumFolds(int numFolds)
Sets the number of folds for cross-validation. A number less than 2 specifies using training error rather than cross-validation.- Parameters:
numFolds
- the number of folds for cross-validation
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debugTipText
public java.lang.String debugTipText()
Returns the tip text for this property- Overrides:
debugTipText
in classClassifier
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setDebug
public void setDebug(boolean debug)
Set debugging mode- Overrides:
setDebug
in classClassifier
- Parameters:
debug
- true if debug output should be printed
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getDebug
public boolean getDebug()
Get whether debugging is turned on- Overrides:
getDebug
in classClassifier
- Returns:
- true if debugging output is on
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getBestClassifierIndex
public int getBestClassifierIndex()
Get the index of the classifier that was determined as best during cross-validation.- Returns:
- the index in the classifier array
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buildClassifier
public void buildClassifier(Instances data) throws java.lang.Exception
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.- Specified by:
buildClassifier
in classClassifier
- Parameters:
data
- the training data to be used for generating the boosted classifier.- Throws:
java.lang.Exception
- if the classifier could not be built successfully
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distributionForInstance
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
Returns class probabilities.- Overrides:
distributionForInstance
in classClassifier
- Parameters:
instance
- the instance to be classified- Returns:
- the distribution for the instance
- Throws:
java.lang.Exception
- if instance could not be classified successfully
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toString
public java.lang.String toString()
Output a representation of this classifier- Overrides:
toString
in classjava.lang.Object
- Returns:
- a string representation of the classifier
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classClassifier
- Returns:
- the revision
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main
public static void main(java.lang.String[] argv)
Main method for testing this class.- Parameters:
argv
- should contain the following arguments: -t training file [-T test file] [-c class index]
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