Class LinearRegression

Method Details

• turnChecksOff

  public void turnChecksOff()

  Turns off checks for missing values, etc. Use with caution. Also turns off scaling.

• turnChecksOn

  public void turnChecksOn()

  Turns on checks for missing values, etc. Also turns on scaling.

• globalInfo

  public String globalInfo()

  Returns a string describing this classifier

  Returns:

  a description of the classifier suitable for displaying in the explorer/experimenter gui

• 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

• buildClassifier

  public void buildClassifier(Instances data) throws Exception

  Builds a regression model for the given data.

  Specified by:

  buildClassifier in class Classifier

  Parameters:

  data - the training data to be used for generating the linear regression function

  Throws:

  Exception - if the classifier could not be built successfully

• classifyInstance

  public double classifyInstance(Instance instance) throws Exception

  Classifies the given instance using the linear regression function.

  Overrides:

  classifyInstance in class Classifier

  Parameters:

  instance - the test instance

  Returns:

  the classification

  Throws:

  Exception - if classification can't be done successfully

• toString

  public String toString()

  Outputs the linear regression model as a string.

  Overrides:

  toString in class Object

  Returns:

  the model as string

• 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
    Produce debugging output.
    (default no debugging output)

   -S <number of selection method>
    Set the attribute selection method to use. 1 = None, 2 = Greedy.
    (default 0 = M5' method)

   -C
    Do not try to eliminate colinear attributes.
   

   -R <double>
    Set ridge parameter (default 1.0e-8).
   

  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

• coefficients

  public double[] coefficients()

  Returns the coefficients for this linear model.

  Returns:

  the coefficients for this linear model

• 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

• ridgeTipText

  public String ridgeTipText()

  Returns the tip text for this property

  Returns:

  tip text for this property suitable for displaying in the explorer/experimenter gui

• getRidge

  public double getRidge()

  Get the value of Ridge.

  Returns:

  Value of Ridge.

• setRidge

  public void setRidge(double newRidge)

  Set the value of Ridge.

  Parameters:

  newRidge - Value to assign to Ridge.

• eliminateColinearAttributesTipText

  public String eliminateColinearAttributesTipText()

  Returns the tip text for this property

  Returns:

  tip text for this property suitable for displaying in the explorer/experimenter gui

• getEliminateColinearAttributes

  public boolean getEliminateColinearAttributes()

  Get the value of EliminateColinearAttributes.

  Returns:

  Value of EliminateColinearAttributes.

• setEliminateColinearAttributes

  public void setEliminateColinearAttributes(boolean newEliminateColinearAttributes)

  Set the value of EliminateColinearAttributes.

  Parameters:

  newEliminateColinearAttributes - Value to assign to EliminateColinearAttributes.

• numParameters

  public int numParameters()

  Get the number of coefficients used in the model

  Returns:

  the number of coefficients

• attributeSelectionMethodTipText

  public String attributeSelectionMethodTipText()

  Returns the tip text for this property

  Returns:

  tip text for this property suitable for displaying in the explorer/experimenter gui

• setAttributeSelectionMethod

  public void setAttributeSelectionMethod(SelectedTag method)

  Sets the method used to select attributes for use in the linear regression.

  Parameters:

  method - the attribute selection method to use.

• getAttributeSelectionMethod

  public SelectedTag getAttributeSelectionMethod()

  Gets the method used to select attributes for use in the linear regression.

  Returns:

  the method to use.

• debugTipText

  public String debugTipText()

  Returns the tip text for this property

  Overrides:

  debugTipText in class Classifier

  Returns:

  tip text for this property suitable for displaying in the explorer/experimenter gui

• setDebug

  public void setDebug(boolean debug)

  Controls whether debugging output will be printed

  Overrides:

  setDebug in class Classifier

  Parameters:

  debug - true if debugging output should be printed

• getDebug

  public boolean getDebug()

  Controls whether debugging output will be printed

  Overrides:

  getDebug in class Classifier

  Returns:

  true if debugging output is printed

• 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)

  Generates a linear regression function predictor.

  Parameters:

  argv - the options