KernelFilter (weka-stable 3.6.8 API)

java.lang.Object
- weka.filters.Filter
- - weka.filters.SimpleFilter
  - - weka.filters.SimpleBatchFilter
    - - weka.filters.unsupervised.attribute.KernelFilter

All Implemented Interfaces:: Serializable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, UnsupervisedFilter

public class KernelFilter
extends SimpleBatchFilter
implements UnsupervisedFilter, TechnicalInformationHandler

Converts the given set of predictor variables into a kernel matrix. The class value remains unchangedm, as long as the preprocessing filter doesn't change it.
By default, the data is preprocessed with the Center filter, but the user can choose any filter (NB: one must be careful that the filter does not alter the class attribute unintentionally). With weka.filters.AllFilter the preprocessing gets disabled.

For more information regarding preprocessing the data, see:

K.P. Bennett, M.J. Embrechts: An Optimization Perspective on Kernel Partial Least Squares Regression. In: Advances in Learning Theory: Methods, Models and Applications, 227-249, 2003.

BibTeX:

 @inproceedings{Bennett2003,
    author = {K.P. Bennett and M.J. Embrechts},
    booktitle = {Advances in Learning Theory: Methods, Models and Applications},
    editor = {J. Suykens et al.},
    pages = {227-249},
    publisher = {IOS Press, Amsterdam, The Netherlands},
    series = {NATO Science Series, Series III: Computer and System Sciences},
    title = {An Optimization Perspective on Kernel Partial Least Squares Regression},
    volume = {190},
    year = {2003}
 }

Valid options are:

 -D
  Turns on output of debugging information.

 -no-checks
  Turns off all checks - use with caution!
  Turning them off assumes that data is purely numeric, doesn't
  contain any missing values, and has a nominal class. Turning them
  off also means that no header information will be stored if the
  machine is linear. Finally, it also assumes that no instance has
  a weight equal to 0.
  (default: checks on)

 -F <filename>
  The file to initialize the filter with (optional).

 -C <num>
  The class index for the file to initialize with,
  First and last are valid (optional, default: last).

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

 -kernel-factor
  Defines a factor for the kernel.
   - RBFKernel: a factor for gamma
    Standardize: 1/(2*N)
    Normalize..: 6/N
  Available parameters are:
   N for # of instances, A for # of attributes
  (default: 1)

 -P <classname and parameters>
  The Filter used for preprocessing (use weka.filters.AllFilter
  to disable preprocessing).
  (default: weka.filters.unsupervised.attribute.Center)

 
 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)

 
 Options specific to preprocessing filter weka.filters.unsupervised.attribute.Center:

 -unset-class-temporarily
  Unsets the class index temporarily before the filter is
  applied to the data.
  (default: no)

Version:: $Revision: 5543 $
Author:: Jonathan Miles (jdm18@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`protected Filter`	`m_ActualFilter` for centering/standardizing the data (the actual filter to use)
`protected Kernel`	`m_ActualKernel` the Kernel which is actually used for computation
`protected boolean`	`m_checksTurnedOff` Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class.
`protected Filter`	`m_Filter` for centering/standardizing the data
`protected File`	`m_InitFile` The dataset to initialize the filter with
`protected SingleIndex`	`m_InitFileClassIndex` the class index for the file to initialized with
`protected boolean`	`m_Initialized` whether the filter was initialized
`protected Kernel`	`m_Kernel` Kernel to use
`protected double`	`m_KernelFactor` the calculated kernel factor
`protected String`	`m_KernelFactorExpression` optimizes the kernel with this formula (A = # of attributes, N = # of instances)
`protected ReplaceMissingValues`	`m_Missing` The filter used to get rid of missing values.
`protected NominalToBinary`	`m_NominalToBinary` The filter used to make attributes numeric.
`protected int`	`m_NumTrainInstances` The number of instances in the training data.

Fields inherited from class weka.filters.SimpleFilter
m_Debug

Fields inherited from class weka.filters.Filter
m_FirstBatchDone, m_InputRelAtts, m_InputStringAtts, m_NewBatch, m_OutputRelAtts, m_OutputStringAtts

Constructor Summary

Constructors
Constructor and Description

KernelFilter()

Constructors
Constructor and Description
`KernelFilter()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`String`	`checksTurnedOffTipText()` Returns the tip text for this property
`protected Instances`	`determineOutputFormat(Instances inputFormat)` Determines the output format based on the input format and returns this.
`Capabilities`	`getCapabilities()` Returns the Capabilities of this filter.
`boolean`	`getChecksTurnedOff()` Returns whether the checks are turned off or not.
`File`	`getInitFile()` Gets the file to initialize the filter with, can be null.
`String`	`getInitFileClassIndex()` Gets the class index of the file to initialize the filter with.
`Kernel`	`getKernel()` Gets the kernel to use.
`String`	`getKernelFactorExpression()` Gets the expression for the kernel.
`String[]`	`getOptions()` Gets the current settings of the filter.
`Filter`	`getPreprocessing()` Gets the filter used for preprocessing
`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`	`initFileClassIndexTipText()` Returns the tip text for this property
`String`	`initFileTipText()` Returns the tip text for this property
`void`	`initFilter(Instances instances)` initializes the filter with the given dataset, i.e., the kernel gets built.
`String`	`kernelFactorExpressionTipText()` Returns the tip text for this property
`String`	`kernelTipText()` Returns the tip text for this property
`Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(String[] args)` runs the filter with the given arguments
`String`	`preprocessingTipText()` Returns the tip text for this property
`protected Instances`	`process(Instances instances)` Processes the given data (may change the provided dataset) and returns the modified version.
`protected void`	`reset()` resets the filter, i.e., m_NewBatch to true and m_FirstBatchDone to false.
`void`	`setChecksTurnedOff(boolean value)` Disables or enables the checks (which could be time-consuming).
`void`	`setInitFile(File value)` Sets the file to initialize the filter with, can be null.
`void`	`setInitFileClassIndex(String value)` Sets class index of the file to initialize the filter with.
`void`	`setKernel(Kernel value)` Sets the kernel to use.
`void`	`setKernelFactorExpression(String value)` Sets the expression for the kernel.
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setPreprocessing(Filter value)` Sets the filter to use for preprocessing (use the AllFilter for no preprocessing)

Methods inherited from class weka.filters.SimpleBatchFilter
batchFinished, hasImmediateOutputFormat, input

Methods inherited from class weka.filters.SimpleFilter
debugTipText, getDebug, setDebug, setInputFormat

Methods inherited from class weka.filters.Filter
batchFilterFile, bufferInput, copyValues, copyValues, filterFile, flushInput, getCapabilities, getInputFormat, getOutputFormat, initInputLocators, initOutputLocators, inputFormatPeek, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, numPendingOutput, output, outputFormatPeek, outputPeek, push, resetQueue, runFilter, setOutputFormat, testInputFormat, toString, useFilter, wekaStaticWrapper

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

- Field Detail
  - m_NumTrainInstances
```
protected int m_NumTrainInstances
```
    The number of instances in the training data.
  - m_Kernel
```
protected Kernel m_Kernel
```
    Kernel to use
  - m_ActualKernel
```
protected Kernel m_ActualKernel
```
    the Kernel which is actually used for computation
  - m_checksTurnedOff
```
protected boolean m_checksTurnedOff
```
    Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class. Turning them off also means that no header information will be stored if the machine is linear. Finally, it also assumes that no instance has a weight equal to 0.
  - m_NominalToBinary
```
protected NominalToBinary m_NominalToBinary
```
    The filter used to make attributes numeric.
  - m_Missing
```
protected ReplaceMissingValues m_Missing
```
    The filter used to get rid of missing values.
  - m_InitFile
```
protected File m_InitFile
```
    The dataset to initialize the filter with
  - m_InitFileClassIndex
```
protected SingleIndex m_InitFileClassIndex
```
    the class index for the file to initialized with
    
    See Also:
    
    m_InitFile
  - m_Initialized
```
protected boolean m_Initialized
```
    whether the filter was initialized
  - m_KernelFactorExpression
```
protected String m_KernelFactorExpression
```
    optimizes the kernel with this formula (A = # of attributes, N = # of instances)
  - m_KernelFactor
```
protected double m_KernelFactor
```
    the calculated kernel factor
    
    See Also:
    
    m_KernelFactorExpression
  - m_Filter
```
protected Filter m_Filter
```
    for centering/standardizing the data
  - m_ActualFilter
```
protected Filter m_ActualFilter
```
    for centering/standardizing the data (the actual filter to use)
- Constructor Detail
  - KernelFilter
```
public KernelFilter()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing this filter.
    
    Specified by:
    
    globalInfo in class SimpleFilter
    
    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 SimpleFilter
    
    Returns:
    
    an enumeration of all the available options.
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the filter.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class SimpleFilter
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options.
    Valid options are:
```
 -D
  Turns on output of debugging information.
```
```
 -no-checks
  Turns off all checks - use with caution!
  Turning them off assumes that data is purely numeric, doesn't
  contain any missing values, and has a nominal class. Turning them
  off also means that no header information will be stored if the
  machine is linear. Finally, it also assumes that no instance has
  a weight equal to 0.
  (default: checks on)
```
```
 -F <filename>
  The file to initialize the filter with (optional).
```
```
 -C <num>
  The class index for the file to initialize with,
  First and last are valid (optional, default: last).
```
```
 -K <classname and parameters>
  The Kernel to use.
  (default: weka.classifiers.functions.supportVector.PolyKernel)
```
```
 -kernel-factor
  Defines a factor for the kernel.
   - RBFKernel: a factor for gamma
    Standardize: 1/(2*N)
    Normalize..: 6/N
  Available parameters are:
   N for # of instances, A for # of attributes
  (default: 1)
```
```
 -P <classname and parameters>
  The Filter used for preprocessing (use weka.filters.AllFilter
  to disable preprocessing).
  (default: weka.filters.unsupervised.attribute.Center)
```
```
 
 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)
```
```
 
 Options specific to preprocessing filter weka.filters.unsupervised.attribute.Center:
 
```
```
 -unset-class-temporarily
  Unsets the class index temporarily before the filter is
  applied to the data.
  (default: no)
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class SimpleFilter
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
    
    See Also:
    
    SimpleFilter.reset()
  - initFileTipText
```
public String initFileTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getInitFile
```
public File getInitFile()
```
    Gets the file to initialize the filter with, can be null.
    
    Returns:
    
    the file
  - setInitFile
```
public void setInitFile(File value)
```
    Sets the file to initialize the filter with, can be null.
    
    Parameters:
    
    value - the file
  - initFileClassIndexTipText
```
public String initFileClassIndexTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getInitFileClassIndex
```
public String getInitFileClassIndex()
```
    Gets the class index of the file to initialize the filter with.
    
    Returns:
    
    the class index
  - setInitFileClassIndex
```
public void setInitFileClassIndex(String value)
```
    Sets class index of the file to initialize the filter with.
    
    Parameters:
    
    value - the class index
  - 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
  - setChecksTurnedOff
```
public void setChecksTurnedOff(boolean value)
```
    Disables or enables the checks (which could be time-consuming). Use with caution!
    
    Parameters:
    
    value - if true turns off all checks
  - getChecksTurnedOff
```
public boolean getChecksTurnedOff()
```
    Returns whether the checks are turned off or not.
    
    Returns:
    
    true if the checks are turned off
  - checksTurnedOffTipText
```
public String checksTurnedOffTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - kernelFactorExpressionTipText
```
public String kernelFactorExpressionTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getKernelFactorExpression
```
public String getKernelFactorExpression()
```
    Gets the expression for the kernel.
    
    Returns:
    
    the expression
  - setKernelFactorExpression
```
public void setKernelFactorExpression(String value)
```
    Sets the expression for the kernel.
    
    Parameters:
    
    value - the file
  - preprocessingTipText
```
public String preprocessingTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setPreprocessing
```
public void setPreprocessing(Filter value)
```
    Sets the filter to use for preprocessing (use the AllFilter for no preprocessing)
    
    Parameters:
    
    value - the preprocessing filter
  - getPreprocessing
```
public Filter getPreprocessing()
```
    Gets the filter used for preprocessing
    
    Returns:
    
    the current preprocessing filter.
  - reset
```
protected void reset()
```
    resets the filter, i.e., m_NewBatch to true and m_FirstBatchDone to false.
    
    Overrides:
    
    reset in class SimpleFilter
    
    See Also:
    
    Filter.m_NewBatch, Filter.m_FirstBatchDone
  - determineOutputFormat
```
protected Instances determineOutputFormat(Instances inputFormat)
                                   throws Exception
```
    Determines the output format based on the input format and returns this. In case the output format cannot be returned immediately, i.e., immediateOutputFormat() returns false, then this method will be called from batchFinished().
    
    Specified by:
    
    determineOutputFormat in class SimpleFilter
    
    Parameters:
    
    inputFormat - the input format to base the output format on
    
    Returns:
    
    the output format
    
    Throws:
    
    Exception - in case the determination goes wrong
    
    See Also:
    
    SimpleBatchFilter.hasImmediateOutputFormat(), SimpleBatchFilter.batchFinished()
  - initFilter
```
public void initFilter(Instances instances)
                throws Exception
```
    initializes the filter with the given dataset, i.e., the kernel gets built. Needs to be called before the first call of Filter.useFilter or batchFinished(), if not the -F option (or setInitFile(File) is used).
    
    Parameters:
    
    instances - the data to initialize with
    
    Throws:
    
    Exception - if building of kernel fails
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns the Capabilities of this filter.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Filter
    
    Returns:
    
    the capabilities of this object
    
    See Also:
    
    Capabilities
  - process
```
protected Instances process(Instances instances)
                     throws Exception
```
    Processes the given data (may change the provided dataset) and returns the modified version. This method is called in batchFinished().
    
    Specified by:
    
    process in class SimpleFilter
    
    Parameters:
    
    instances - the data to process
    
    Returns:
    
    the modified data
    
    Throws:
    
    Exception - in case the processing goes wrong
    
    See Also:
    
    SimpleBatchFilter.batchFinished()
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Filter
    
    Returns:
    
    the revision
  - main
```
public static void main(String[] args)
```
    runs the filter with the given arguments
    
    Parameters:
    
    args - the commandline arguments

Class KernelFilter

Field Summary

Fields inherited from class weka.filters.SimpleFilter

Fields inherited from class weka.filters.Filter

Constructor Summary

Method Summary

Methods inherited from class weka.filters.SimpleBatchFilter

Methods inherited from class weka.filters.SimpleFilter

Methods inherited from class weka.filters.Filter

Methods inherited from class java.lang.Object

Field Detail

m_NumTrainInstances

m_Kernel

m_ActualKernel

m_checksTurnedOff

m_NominalToBinary

m_Missing

m_InitFile

m_InitFileClassIndex

m_Initialized

m_KernelFactorExpression

m_KernelFactor

m_Filter

m_ActualFilter

Constructor Detail

KernelFilter

Method Detail

globalInfo

getTechnicalInformation

listOptions

getOptions

setOptions

initFileTipText

getInitFile

setInitFile

initFileClassIndexTipText

getInitFileClassIndex

setInitFileClassIndex

kernelTipText

getKernel

setKernel

setChecksTurnedOff

getChecksTurnedOff

checksTurnedOffTipText

kernelFactorExpressionTipText

getKernelFactorExpression

setKernelFactorExpression

preprocessingTipText

setPreprocessing

getPreprocessing

reset

determineOutputFormat

initFilter

getCapabilities

process

getRevision

main