Class SimpleLinearRegression

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.functions.SimpleLinearRegression
All Implemented Interfaces:
Serializable, Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, WeightedInstancesHandler

public class SimpleLinearRegression extends Classifier implements WeightedInstancesHandler
Learns a simple linear regression model. Picks the attribute that results in the lowest squared error. Missing values are not allowed. Can only deal with numeric attributes.

Valid options are:

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
Version:
$Revision: 5523 $
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
    • classifyInstance

      public double classifyInstance(Instance inst) throws Exception
      Generate a prediction for the supplied instance.
      Overrides:
      classifyInstance in class Classifier
      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
      Overrides:
      getCapabilities in class Classifier
      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 class 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 Classifier
      Returns:
      the revision
    • main

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