MISVM (weka-stable 3.6.14 API)

java.lang.Object
- weka.classifiers.Classifier
- - weka.classifiers.mi.MISVM

All Implemented Interfaces:: Serializable, Cloneable, CapabilitiesHandler, MultiInstanceCapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class MISVM
extends Classifier
implements OptionHandler, MultiInstanceCapabilitiesHandler, TechnicalInformationHandler

Implements Stuart Andrews' mi_SVM (Maximum pattern Margin Formulation of MIL). Applying weka.classifiers.functions.SMO to solve multiple instances problem.
The algorithm first assign the bag label to each instance in the bag as its initial class label. After that applying SMO to compute SVM solution for all instances in positive bags And then reassign the class label of each instance in the positive bag according to the SVM result Keep on iteration until labels do not change anymore.

For more information see:

Stuart Andrews, Ioannis Tsochantaridis, Thomas Hofmann: Support Vector Machines for Multiple-Instance Learning. In: Advances in Neural Information Processing Systems 15, 561-568, 2003.

BibTeX:

 @inproceedings{Andrews2003,
    author = {Stuart Andrews and Ioannis Tsochantaridis and Thomas Hofmann},
    booktitle = {Advances in Neural Information Processing Systems 15},
    pages = {561-568},
    publisher = {MIT Press},
    title = {Support Vector Machines for Multiple-Instance Learning},
    year = {2003}
 }

Valid options are:

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

 -C <double>
  The complexity constant C. (default 1)

 -N <default 0>
  Whether to 0=normalize/1=standardize/2=neither.
  (default: 0=normalize)

 -I <num>
  The maximum number of iterations to perform.
  (default: 500)

 -K <classname and parameters>
  The Kernel to use.
  (default: weka.classifiers.functions.supportVector.PolyKernel)

 
 Options specific to kernel weka.classifiers.functions.supportVector.PolyKernel:

 -D
  Enables debugging output (if available) to be printed.
  (default: off)

 -no-checks
  Turns off all checks - use with caution!
  (default: checks on)

 -C <num>
  The size of the cache (a prime number), 0 for full cache and 
  -1 to turn it off.
  (default: 250007)

 -E <num>
  The Exponent to use.
  (default: 1.0)

 -L
  Use lower-order terms.
  (default: no)

Version:: $Revision: 9144 $
Author:: Lin Dong ([email protected])
See Also:: SMO, Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static int`	`FILTER_NONE` No normalization/standardization
`static int`	`FILTER_NORMALIZE` Normalize training data
`static int`	`FILTER_STANDARDIZE` Standardize training data
`static Tag[]`	`TAGS_FILTER` The filter to apply to the training data

Constructor Summary

Constructors
Constructor and Description

MISVM()

Constructors
Constructor and Description
`MISVM()`

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`buildClassifier(Instances train)` Builds the classifier
`String`	`cTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance exmp)` Computes the distribution for a given exemplar
`String`	`filterTypeTipText()` Returns the tip text for this property
`double`	`getC()` Get the value of C.
`Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`SelectedTag`	`getFilterType()` Gets how the training data will be transformed.
`Kernel`	`getKernel()` Gets the kernel to use.
`int`	`getMaxIterations()` Gets the maximum number of iterations.
`Capabilities`	`getMultiInstanceCapabilities()` Returns the capabilities of this multi-instance classifier for the relational data.
`String[]`	`getOptions()` Gets the current settings of the classifier.
`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.
`String`	`globalInfo()` Returns a string describing this filter
`String`	`kernelTipText()` Returns the tip text for this property
`Enumeration`	`listOptions()` Returns an enumeration describing the available options
`static void`	`main(String[] argv)` Main method for testing this class.
`String`	`maxIterationsTipText()` Returns the tip text for this property
`void`	`setC(double v)` Set the value of C.
`void`	`setFilterType(SelectedTag newType)` Sets how the training data will be transformed.
`void`	`setKernel(Kernel value)` Sets the kernel to use.
`void`	`setMaxIterations(int value)` Sets the maximum number of iterations.
`void`	`setOptions(String[] options)` Parses a given list of options.

Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - FILTER_NORMALIZE
```
public static final int FILTER_NORMALIZE
```
    Normalize training data
    
    See Also:
    Constant Field Values
  - FILTER_STANDARDIZE
```
public static final int FILTER_STANDARDIZE
```
    Standardize training data
    
    See Also:
    Constant Field Values
  - FILTER_NONE
```
public static final int FILTER_NONE
```
    No normalization/standardization
    
    See Also:
    Constant Field Values
  - TAGS_FILTER
```
public static final Tag[] TAGS_FILTER
```
    The filter to apply to the training data
- Constructor Detail
  - MISVM
```
public MISVM()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing this filter
    
    Returns:
    a description of the filter suitable for displaying in the explorer/experimenter gui
  - 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 interface TechnicalInformationHandler
    
    Returns:
    the technical information about this class
  - listOptions
```
public Enumeration listOptions()
```
    Returns an enumeration describing the available options
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class Classifier
    
    Returns:
    an enumeration of all the available options
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options.
    Valid options are:
```
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
```
```
 -C <double>
  The complexity constant C. (default 1)
```
```
 -N <default 0>
  Whether to 0=normalize/1=standardize/2=neither.
  (default: 0=normalize)
```
```
 -I <num>
  The maximum number of iterations to perform.
  (default: 500)
```
```
 -K <classname and parameters>
  The Kernel to use.
  (default: weka.classifiers.functions.supportVector.PolyKernel)
```
```
 
 Options specific to kernel weka.classifiers.functions.supportVector.PolyKernel:
 
```
```
 -D
  Enables debugging output (if available) to be printed.
  (default: off)
```
```
 -no-checks
  Turns off all checks - use with caution!
  (default: checks on)
```
```
 -C <num>
  The size of the cache (a prime number), 0 for full cache and 
  -1 to turn it off.
  (default: 250007)
```
```
 -E <num>
  The Exponent to use.
  (default: 1.0)
```
```
 -L
  Use lower-order terms.
  (default: no)
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class Classifier
    
    Parameters:
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the classifier.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class Classifier
    
    Returns:
    an array of strings suitable for passing to setOptions
  - kernelTipText
```
public String kernelTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getKernel
```
public Kernel getKernel()
```
    Gets the kernel to use.
    
    Returns:
    the kernel
  - setKernel
```
public void setKernel(Kernel value)
```
    Sets the kernel to use.
    
    Parameters:
    value - the kernel
  - filterTypeTipText
```
public String filterTypeTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setFilterType
```
public void setFilterType(SelectedTag newType)
```
    Sets how the training data will be transformed. Should be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
    
    Parameters:
    newType - the new filtering mode
  - getFilterType
```
public SelectedTag getFilterType()
```
    Gets how the training data will be transformed. Will be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
    
    Returns:
    the filtering mode
  - cTipText
```
public String cTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getC
```
public double getC()
```
    Get the value of C.
    
    Returns:
    Value of C.
  - setC
```
public void setC(double v)
```
    Set the value of C.
    
    Parameters:
    v - Value to assign to C.
  - maxIterationsTipText
```
public String maxIterationsTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getMaxIterations
```
public int getMaxIterations()
```
    Gets the maximum number of iterations.
    
    Returns:
    the maximum number of iterations.
  - setMaxIterations
```
public void setMaxIterations(int value)
```
    Sets the maximum number of iterations.
    
    Parameters:
    value - the maximum number of iterations.
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the classifier.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Classifier
    
    Returns:
    the capabilities of this classifier
    See Also:
    Capabilities
  - getMultiInstanceCapabilities
```
public Capabilities getMultiInstanceCapabilities()
```
    Returns the capabilities of this multi-instance classifier for the relational data.
    
    Specified by:
    
    getMultiInstanceCapabilities in interface MultiInstanceCapabilitiesHandler
    
    Returns:
    the capabilities of this object
    See Also:
    Capabilities
  - buildClassifier
```
public void buildClassifier(Instances train)
                     throws Exception
```
    Builds the classifier
    
    Specified by:
    
    buildClassifier in class Classifier
    
    Parameters:
    train - the training data to be used for generating the boosted classifier.
    
    Throws:
    
    Exception - if the classifier could not be built successfully
  - distributionForInstance
```
public double[] distributionForInstance(Instance exmp)
                                 throws Exception
```
    Computes the distribution for a given exemplar
    
    Overrides:
    
    distributionForInstance in class Classifier
    
    Parameters:
    exmp - the exemplar for which distribution is computed
    
    Returns:
    the distribution
    
    Throws:
    
    Exception - if the distribution can't be computed successfully
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Classifier
    
    Returns:
    the revision
  - main
```
public static void main(String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    argv - should contain the command line arguments to the scheme (see Evaluation)

Class MISVM

Field Summary

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Field Detail

FILTER_NORMALIZE

FILTER_STANDARDIZE

FILTER_NONE

TAGS_FILTER

Constructor Detail

MISVM

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

getOptions

kernelTipText

getKernel

setKernel

filterTypeTipText

setFilterType

getFilterType

cTipText

getC

setC

maxIterationsTipText

getMaxIterations

setMaxIterations

getCapabilities

getMultiInstanceCapabilities

buildClassifier

distributionForInstance

getRevision

main