Package weka.classifiers.lazy
Class KStar
- java.lang.Object
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- weka.classifiers.Classifier
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- weka.classifiers.lazy.KStar
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- All Implemented Interfaces:
java.io.Serializable
,java.lang.Cloneable
,KStarConstants
,UpdateableClassifier
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class KStar extends Classifier implements KStarConstants, UpdateableClassifier, TechnicalInformationHandler
K* is an instance-based classifier, that is the class of a test instance is based upon the class of those training instances similar to it, as determined by some similarity function. It differs from other instance-based learners in that it uses an entropy-based distance function.
For more information on K*, see
John G. Cleary, Leonard E. Trigg: K*: An Instance-based Learner Using an Entropic Distance Measure. In: 12th International Conference on Machine Learning, 108-114, 1995. BibTeX:@inproceedings{Cleary1995, author = {John G. Cleary and Leonard E. Trigg}, booktitle = {12th International Conference on Machine Learning}, pages = {108-114}, title = {K*: An Instance-based Learner Using an Entropic Distance Measure}, year = {1995} }
Valid options are:-B <num> Manual blend setting (default 20%)
-E Enable entropic auto-blend setting (symbolic class only)
-M <char> Specify the missing value treatment mode (default a) Valid options are: a(verage), d(elete), m(axdiff), n(ormal)
- Version:
- $Revision: 5525 $
- Author:
- Len Trigg (len@reeltwo.com), Abdelaziz Mahoui (am14@cs.waikato.ac.nz) - Java port
- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field Description static Tag[]
TAGS_MISSING
Define possible missing value handling methods-
Fields inherited from interface weka.classifiers.lazy.kstar.KStarConstants
B_ENTROPY, B_SPHERE, EPSILON, FLOOR, FLOOR1, INITIAL_STEP, LOG2, M_AVERAGE, M_DELETE, M_MAXDIFF, M_NORMAL, NUM_RAND_COLS, OFF, ON, ROOT_FINDER_ACCURACY, ROOT_FINDER_MAX_ITER
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Constructor Summary
Constructors Constructor Description KStar()
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description void
buildClassifier(Instances instances)
Generates the classifier.double[]
distributionForInstance(Instance instance)
Calculates the class membership probabilities for the given test instance.java.lang.String
entropicAutoBlendTipText()
Returns the tip text for this propertyCapabilities
getCapabilities()
Returns default capabilities of the classifier.boolean
getEntropicAutoBlend()
Get whether entropic blending being usedint
getGlobalBlend()
Get the value of the global blend parameterSelectedTag
getMissingMode()
Gets the method to use for handling missing values.java.lang.String[]
getOptions()
Gets the current settings of K*.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
globalBlendTipText()
Returns the tip text for this propertyjava.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
missingModeTipText()
Returns the tip text for this propertyvoid
setEntropicAutoBlend(boolean e)
Set whether entropic blending is to be used.void
setGlobalBlend(int b)
Set the global blend parametervoid
setMissingMode(SelectedTag newMode)
Sets the method to use for handling missing values.void
setOptions(java.lang.String[] options)
Parses a given list of options.java.lang.String
toString()
Returns a description of this classifier.void
updateClassifier(Instance instance)
Adds the supplied instance to the training set-
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
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Field Detail
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TAGS_MISSING
public static final Tag[] TAGS_MISSING
Define possible missing value handling methods
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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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getTechnicalInformation
public 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.- Specified by:
getTechnicalInformation
in interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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getCapabilities
public Capabilities getCapabilities()
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classClassifier
- Returns:
- the capabilities of this classifier
- See Also:
Capabilities
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buildClassifier
public void buildClassifier(Instances instances) throws java.lang.Exception
Generates the classifier.- Specified by:
buildClassifier
in classClassifier
- Parameters:
instances
- set of instances serving as training data- Throws:
java.lang.Exception
- if the classifier has not been generated successfully
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updateClassifier
public void updateClassifier(Instance instance) throws java.lang.Exception
Adds the supplied instance to the training set- Specified by:
updateClassifier
in interfaceUpdateableClassifier
- Parameters:
instance
- the instance to add- Throws:
java.lang.Exception
- if instance could not be incorporated successfully
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distributionForInstance
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
Calculates the class membership probabilities for the given test instance.- Overrides:
distributionForInstance
in classClassifier
- Parameters:
instance
- the instance to be classified- Returns:
- predicted class probability distribution
- Throws:
java.lang.Exception
- if an error occurred during the prediction
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missingModeTipText
public java.lang.String missingModeTipText()
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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getMissingMode
public SelectedTag getMissingMode()
Gets the method to use for handling missing values. Will be one of M_NORMAL, M_AVERAGE, M_MAXDIFF or M_DELETE.- Returns:
- the method used for handling missing values.
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setMissingMode
public void setMissingMode(SelectedTag newMode)
Sets the method to use for handling missing values. Values other than M_NORMAL, M_AVERAGE, M_MAXDIFF and M_DELETE will be ignored.- Parameters:
newMode
- the method to use for handling missing values.
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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 classClassifier
- Returns:
- an enumeration of all the available options.
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globalBlendTipText
public java.lang.String globalBlendTipText()
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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setGlobalBlend
public void setGlobalBlend(int b)
Set the global blend parameter- Parameters:
b
- the value for global blending
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getGlobalBlend
public int getGlobalBlend()
Get the value of the global blend parameter- Returns:
- the value of the global blend parameter
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entropicAutoBlendTipText
public java.lang.String entropicAutoBlendTipText()
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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setEntropicAutoBlend
public void setEntropicAutoBlend(boolean e)
Set whether entropic blending is to be used.- Parameters:
e
- true if entropic blending is to be used
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getEntropicAutoBlend
public boolean getEntropicAutoBlend()
Get whether entropic blending being used- Returns:
- true if entropic blending is used
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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:-B <num> Manual blend setting (default 20%)
-E Enable entropic auto-blend setting (symbolic class only)
-M <char> Specify the missing value treatment mode (default a) Valid options are: a(verage), d(elete), m(axdiff), n(ormal)
- Specified by:
setOptions
in interfaceOptionHandler
- Overrides:
setOptions
in classClassifier
- 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 K*.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classClassifier
- Returns:
- an array of strings suitable for passing to setOptions()
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toString
public java.lang.String toString()
Returns a description of this classifier.- Overrides:
toString
in classjava.lang.Object
- Returns:
- a description of this classifier as a string.
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main
public static void main(java.lang.String[] argv)
Main method for testing this class.- Parameters:
argv
- should contain command line options (see setOptions)
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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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