类 SMOreg

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.functions.SMOreg
所有已实现的接口:
Serializable, Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

SMOreg implements the support vector machine for regression. The parameters can be learned using various algorithms. The algorithm is selected by setting the RegOptimizer. The most popular algorithm (RegSMOImproved) is due to Shevade, Keerthi et al and this is the default RegOptimizer.

For more information see:

S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy: Improvements to the SMO Algorithm for SVM Regression. In: IEEE Transactions on Neural Networks, 1999.

A.J. Smola, B. Schoelkopf (1998). A tutorial on support vector regression.

BibTeX:

 @inproceedings{Shevade1999,
    author = {S.K. Shevade and S.S. Keerthi and C. Bhattacharyya and K.R.K. Murthy},
    booktitle = {IEEE Transactions on Neural Networks},
    title = {Improvements to the SMO Algorithm for SVM Regression},
    year = {1999},
    PS = {http://guppy.mpe.nus.edu.sg/\~mpessk/svm/ieee_smo_reg.ps.gz}
 }
 
 @techreport{Smola1998,
    author = {A.J. Smola and B. Schoelkopf},
    note = {NeuroCOLT2 Technical Report NC2-TR-1998-030},
    title = {A tutorial on support vector regression},
    year = {1998}
 }
 

Valid options are:

 -C <double>
  The complexity constant C.
  (default 1)
 -N
  Whether to 0=normalize/1=standardize/2=neither.
  (default 0=normalize)
 -I <classname and parameters>
  Optimizer class used for solving quadratic optimization problem
  (default weka.classifiers.functions.supportVector.RegSMOImproved)
 -K <classname and parameters>
  The Kernel to use.
  (default: weka.classifiers.functions.supportVector.PolyKernel)
 
 Options specific to optimizer ('-I') weka.classifiers.functions.supportVector.RegSMOImproved:
 
 -T <double>
  The tolerance parameter for checking the stopping criterion.
  (default 0.001)
 -V
  Use variant 1 of the algorithm when true, otherwise use variant 2.
  (default true)
 -P <double>
  The epsilon for round-off error.
  (default 1.0e-12)
 -L <double>
  The epsilon parameter in epsilon-insensitive loss function.
  (default 1.0e-3)
 -W <double>
  The random number seed.
  (default 1)
 
 Options specific to kernel ('-K') 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)
版本:
$Revision: 8126 $
作者:
Remco Bouckaert (remco@cs.waikato.ac.nz,rrb@xm.co.nz)
另请参阅:
  • 字段详细资料

    • FILTER_NORMALIZE

      public static final int FILTER_NORMALIZE
      The filter to apply to the training data: Normalzie
      另请参阅:
    • FILTER_STANDARDIZE

      public static final int FILTER_STANDARDIZE
      The filter to apply to the training data: Standardize
      另请参阅:
    • FILTER_NONE

      public static final int FILTER_NONE
      The filter to apply to the training data: None
      另请参阅:
    • TAGS_FILTER

      public static final Tag[] TAGS_FILTER
      The filter to apply to the training data
  • 构造器详细资料

    • SMOreg

      public SMOreg()
  • 方法详细资料

    • globalInfo

      public String globalInfo()
      Returns a string describing classifier
      返回:
      a description 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.
      指定者:
      getTechnicalInformation 在接口中 TechnicalInformationHandler
      返回:
      the technical information about this class
    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options.
      指定者:
      listOptions 在接口中 OptionHandler
      覆盖:
      listOptions 在类中 Classifier
      返回:
      an enumeration of all the available options.
    • setOptions

      public void setOptions(String[] options) throws Exception
      Parses a given list of options.

      Valid options are:

       -C <double>
        The complexity constant C.
        (default 1)
       -N
        Whether to 0=normalize/1=standardize/2=neither.
        (default 0=normalize)
       -I <classname and parameters>
        Optimizer class used for solving quadratic optimization problem
        (default weka.classifiers.functions.supportVector.RegSMOImproved)
       -K <classname and parameters>
        The Kernel to use.
        (default: weka.classifiers.functions.supportVector.PolyKernel)
       
       Options specific to optimizer ('-I') weka.classifiers.functions.supportVector.RegSMOImproved:
       
       -T <double>
        The tolerance parameter for checking the stopping criterion.
        (default 0.001)
       -V
        Use variant 1 of the algorithm when true, otherwise use variant 2.
        (default true)
       -P <double>
        The epsilon for round-off error.
        (default 1.0e-12)
       -L <double>
        The epsilon parameter in epsilon-insensitive loss function.
        (default 1.0e-3)
       -W <double>
        The random number seed.
        (default 1)
       
       Options specific to kernel ('-K') 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)
      指定者:
      setOptions 在接口中 OptionHandler
      覆盖:
      setOptions 在类中 Classifier
      参数:
      options - the list of options as an array of strings
      抛出:
      Exception - if an option is not supported
    • getOptions

      public String[] getOptions()
      Gets the current settings of the classifier.
      指定者:
      getOptions 在接口中 OptionHandler
      覆盖:
      getOptions 在类中 Classifier
      返回:
      an array of strings suitable for passing to setOptions
    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier.
      指定者:
      getCapabilities 在接口中 CapabilitiesHandler
      覆盖:
      getCapabilities 在类中 Classifier
      返回:
      the capabilities of this classifier
      另请参阅:
    • buildClassifier

      public void buildClassifier(Instances instances) throws Exception
      Method for building the classifier.
      指定者:
      buildClassifier 在类中 Classifier
      参数:
      instances - the set of training instances
      抛出:
      Exception - if the classifier can't be built successfully
    • classifyInstance

      public double classifyInstance(Instance instance) throws Exception
      Classifies the given instance using the linear regression function.
      覆盖:
      classifyInstance 在类中 Classifier
      参数:
      instance - the test instance
      返回:
      the classification
      抛出:
      Exception - if classification can't be done successfully
    • regOptimizerTipText

      public String regOptimizerTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setRegOptimizer

      public void setRegOptimizer(RegOptimizer regOptimizer)
      sets the learning algorithm
      参数:
      regOptimizer - the learning algorithm
    • getRegOptimizer

      public RegOptimizer getRegOptimizer()
      returns the learning algorithm
      返回:
      the learning algorithm
    • kernelTipText

      public String kernelTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setKernel

      public void setKernel(Kernel value)
      sets the kernel to use
      参数:
      value - the kernel to use
    • getKernel

      public Kernel getKernel()
      Returns the kernel to use
      返回:
      the current kernel
    • cTipText

      public String cTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getC

      public double getC()
      Get the value of C.
      返回:
      Value of C.
    • setC

      public void setC(double v)
      Set the value of C.
      参数:
      v - Value to assign to C.
    • filterTypeTipText

      public String filterTypeTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getFilterType

      public SelectedTag getFilterType()
      Gets how the training data will be transformed. Will be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
      返回:
      the filtering mode
    • setFilterType

      public void setFilterType(SelectedTag newType)
      Sets how the training data will be transformed. Should be one of FILTER_NORMALIZE, FILTER_STANDARDIZE, FILTER_NONE.
      参数:
      newType - the new filtering mode
    • toString

      public String toString()
      Prints out the classifier.
      覆盖:
      toString 在类中 Object
      返回:
      a description of the classifier as a string
    • enumerateMeasures

      public Enumeration enumerateMeasures()
      Returns an enumeration of the measure names. Additional measures must follow the naming convention of starting with "measure", eg. double measureBlah()
      指定者:
      enumerateMeasures 在接口中 AdditionalMeasureProducer
      返回:
      an enumeration of the measure names
    • getMeasure

      public double getMeasure(String measureName)
      Returns the value of the named measure
      指定者:
      getMeasure 在接口中 AdditionalMeasureProducer
      参数:
      measureName - the name of the measure to query for its value
      返回:
      the value of the named measure
      抛出:
      IllegalArgumentException - if the named measure is not supported
    • getRevision

      public String getRevision()
      Returns the revision string.
      指定者:
      getRevision 在接口中 RevisionHandler
      覆盖:
      getRevision 在类中 Classifier
      返回:
      the revision
    • main

      public static void main(String[] args)
      Main method for running this classifier.
      参数:
      args - the commandline options