Package weka.classifiers.functions

Class SimpleLinearRegression

java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.functions.SimpleLinearRegression
All Implemented Interfaces:
Serializable, Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler, WeightedInstancesHandler
public class SimpleLinearRegression extends AbstractClassifier implements WeightedInstancesHandler
Learns a simple linear regression model. Picks the attribute that results in the lowest squared error. Can only deal with numeric attributes.

Valid options are: 

 -additional-stats
  Output additional statistics.
 
 -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
 
 -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
Version:
$Revision: 15519 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:

  • Constructor Details

    • SimpleLinearRegression

      public SimpleLinearRegression()

  • Method Details

    • globalInfo

      public String globalInfo()
      Returns a string describing this classifier
      Returns:
      a description of the classifier suitable for displaying in the explorer/experimenter gui

    • listOptions

      public Enumeration<Option> listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      Overrides:
      listOptions in class AbstractClassifier
      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: 

       -additional-stats
  Output additional statistics.
 
       -output-debug-info
  If set, classifier is run in debug mode and
  may output additional info to the console
 
       -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).
      Specified by:
      setOptions in interface OptionHandler
      Overrides:
      setOptions in class AbstractClassifier
      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 AbstractClassifier
      Returns:
      an array of strings suitable for passing to setOptions

    • outputAdditionalStatsTipText

      public String outputAdditionalStatsTipText()
      Returns the tip text for this property.
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • setOutputAdditionalStats

      public void setOutputAdditionalStats(boolean additional)
      Set whether to output additional statistics (such as std. deviation of coefficients and t-statistics
      Parameters:
      additional - true if additional stats are to be output

    • getOutputAdditionalStats

      public boolean getOutputAdditionalStats()
      Get whether to output additional statistics (such as std. deviation of coefficients and t-statistics
      Returns:
      true if additional stats are to be output

    • classifyInstance

      public double classifyInstance(Instance inst) throws Exception
      Generate a prediction for the supplied instance.
      Specified by:
      classifyInstance in interface Classifier
      Overrides:
      classifyInstance in class AbstractClassifier
      Parameters:
      inst - the instance to predict.
      Returns:
      the prediction
      Throws:
      Exception - if an error occurs

    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier.
      Specified by:
      getCapabilities in interface CapabilitiesHandler
      Specified by:
      getCapabilities in interface Classifier
      Overrides:
      getCapabilities in class AbstractClassifier
      Returns:
      the capabilities of this classifier
      See Also:

    • buildClassifier

      public void buildClassifier(Instances insts) throws Exception
      Builds a simple linear regression model given the supplied training data.
      Specified by:
      buildClassifier in interface Classifier
      Parameters:
      insts - the training data.
      Throws:
      Exception - if an error occurs

    • foundUsefulAttribute

      public boolean foundUsefulAttribute()
      Returns true if a usable attribute was found.
      Returns:
      true if a usable attribute was found.

    • getAttributeIndex

      public int getAttributeIndex()
      Returns the index of the attribute used in the regression.
      Returns:
      the index of the attribute.

    • getSlope

      public double getSlope()
      Returns the slope of the function.
      Returns:
      the slope.

    • getIntercept

      public double getIntercept()
      Returns the intercept of the function.
      Returns:
      the intercept.

    • setSuppressErrorMessage

      public void setSuppressErrorMessage(boolean s)
      Turn off the error message that is reported when no useful attribute is found.
      Parameters:
      s - if set to true turns off the error message

    • toString

      public String toString()
      Returns a description of this classifier as a string
      Overrides:
      toString in class Object
      Returns:
      a description of the classifier.

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Overrides:
      getRevision in class AbstractClassifier
      Returns:
      the revision

    • main

      public static void main(String[] argv)
      Main method for testing this class
      Parameters:
      argv - options