Package weka.classifiers.mi
Class MIWrapper
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.mi.MIWrapper
- All Implemented Interfaces:
Serializable
,Cloneable
,CapabilitiesHandler
,MultiInstanceCapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class MIWrapper
extends SingleClassifierEnhancer
implements MultiInstanceCapabilitiesHandler, OptionHandler, TechnicalInformationHandler
A simple Wrapper method for applying standard propositional learners to multi-instance data.
For more information see:
E. T. Frank, X. Xu (2003). Applying propositional learning algorithms to multi-instance data. Department of Computer Science, University of Waikato, Hamilton, NZ. BibTeX:
For more information see:
E. T. Frank, X. Xu (2003). Applying propositional learning algorithms to multi-instance data. Department of Computer Science, University of Waikato, Hamilton, NZ. BibTeX:
@techreport{Frank2003, address = {Department of Computer Science, University of Waikato, Hamilton, NZ}, author = {E. T. Frank and X. Xu}, institution = {University of Waikato}, month = {06}, title = {Applying propositional learning algorithms to multi-instance data}, year = {2003} }Valid options are:
-P [1|2|3] The method used in testing: 1.arithmetic average 2.geometric average 3.max probability of positive bag. (default: 1)
-A [0|1|2|3] The type of weight setting for each single-instance: 0.keep the weight to be the same as the original value; 1.weight = 1.0 2.weight = 1.0/Total number of single-instance in the corresponding bag 3. weight = Total number of single-instance / (Total number of bags * Total number of single-instance in the corresponding bag). (default: 3)
-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.rules.ZeroR)
Options specific to classifier weka.classifiers.rules.ZeroR:
-D If set, classifier is run in debug mode and may output additional info to the console
- Version:
- $Revision: 9144 $
- Author:
- Eibe Frank (eibe@cs.waikato.ac.nz), Xin Xu (xx5@cs.waikato.ac.nz)
- See Also:
-
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final Tag[]
the test methodsstatic final int
arithmetic averagestatic final int
geometric averagestatic final int
max probability of positive bag -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoid
buildClassifier
(Instances data) Builds the classifierdouble[]
Computes the distribution for a given exemplarReturns default capabilities of the classifier.Get the method used in testing.Returns the capabilities of this multi-instance classifier for the relational data.String[]
Gets the current settings of the Classifier.Returns the revision string.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.Returns the current weighting method for instances.Returns a string describing this filterReturns an enumeration describing the available options.static void
Main method for testing this class.Returns the tip text for this propertyvoid
setMethod
(SelectedTag method) Set the method used in testing.void
setOptions
(String[] options) Parses a given list of options.void
setWeightMethod
(SelectedTag method) The new method for weighting the instances.toString()
Gets a string describing the classifier.Returns the tip text for this propertyMethods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, setClassifier
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
-
Field Details
-
TESTMETHOD_ARITHMETIC
public static final int TESTMETHOD_ARITHMETICarithmetic average- See Also:
-
TESTMETHOD_GEOMETRIC
public static final int TESTMETHOD_GEOMETRICgeometric average- See Also:
-
TESTMETHOD_MAXPROB
public static final int TESTMETHOD_MAXPROBmax probability of positive bag- See Also:
-
TAGS_TESTMETHOD
the test methods
-
-
Constructor Details
-
MIWrapper
public MIWrapper()
-
-
Method Details
-
globalInfo
Returns a string describing this filter- Returns:
- a description of the filter suitable for displaying in the explorer/experimenter gui
-
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
-
listOptions
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classSingleClassifierEnhancer
- Returns:
- an enumeration of all the available options.
-
setOptions
Parses a given list of options. Valid options are:-P [1|2|3] The method used in testing: 1.arithmetic average 2.geometric average 3.max probability of positive bag. (default: 1)
-A [0|1|2|3] The type of weight setting for each single-instance: 0.keep the weight to be the same as the original value; 1.weight = 1.0 2.weight = 1.0/Total number of single-instance in the corresponding bag 3. weight = Total number of single-instance / (Total number of bags * Total number of single-instance in the corresponding bag). (default: 3)
-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.rules.ZeroR)
Options specific to classifier 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 classSingleClassifierEnhancer
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
-
getOptions
Gets the current settings of the Classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classSingleClassifierEnhancer
- Returns:
- an array of strings suitable for passing to setOptions
-
weightMethodTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
-
setWeightMethod
The new method for weighting the instances.- Parameters:
method
- the new method
-
getWeightMethod
Returns the current weighting method for instances.- Returns:
- the current weighting method
-
methodTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
-
setMethod
Set the method used in testing.- Parameters:
method
- the index of method to use.
-
getMethod
Get the method used in testing.- Returns:
- the index of method used in testing.
-
getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classSingleClassifierEnhancer
- Returns:
- the capabilities of this classifier
- See Also:
-
getMultiInstanceCapabilities
Returns the capabilities of this multi-instance classifier for the relational data.- Specified by:
getMultiInstanceCapabilities
in interfaceMultiInstanceCapabilitiesHandler
- Returns:
- the capabilities of this object
- See Also:
-
buildClassifier
Builds the classifier- Specified by:
buildClassifier
in classClassifier
- Parameters:
data
- the training data to be used for generating the boosted classifier.- Throws:
Exception
- if the classifier could not be built successfully
-
distributionForInstance
Computes the distribution for a given exemplar- Overrides:
distributionForInstance
in classClassifier
- Parameters:
exmp
- the exemplar for which distribution is computed- Returns:
- the distribution
- Throws:
Exception
- if the distribution can't be computed successfully
-
toString
Gets a string describing the classifier. -
getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classClassifier
- Returns:
- the revision
-
main
Main method for testing this class.- Parameters:
argv
- should contain the command line arguments to the scheme (see Evaluation)
-