Class PreConstructedLinearModel

java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.trees.m5.PreConstructedLinearModel
All Implemented Interfaces:
Serializable, Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler

public class PreConstructedLinearModel extends AbstractClassifier implements Serializable
This class encapsulates a linear regression function. It is a classifier but does not learn the function itself, instead it is constructed with coefficients and intercept obtained elsewhere. The buildClassifier method must still be called however as this stores a copy of the training data's header for use in printing the model to the console.
Version:
$Revision: 15357 $
Author:
Mark Hall (mhall@cs.waikato.ac.nz)
See Also:
  • Constructor Details

    • PreConstructedLinearModel

      public PreConstructedLinearModel(double[] coeffs, double intercept)
      Constructor
      Parameters:
      coeffs - an array of coefficients
      intercept - the intercept
  • Method Details

    • buildClassifier

      public void buildClassifier(Instances instances) throws Exception
      Builds the classifier. In this case all that is done is that a copy of the training instances header is saved.
      Specified by:
      buildClassifier in interface Classifier
      Parameters:
      instances - an Instances value
      Throws:
      Exception - if an error occurs
    • classifyInstance

      public double classifyInstance(Instance inst) throws Exception
      Predicts the class of the supplied instance using the linear model.
      Specified by:
      classifyInstance in interface Classifier
      Overrides:
      classifyInstance in class AbstractClassifier
      Parameters:
      inst - the instance to make a prediction for
      Returns:
      the prediction
      Throws:
      Exception - if an error occurs
    • numParameters

      public int numParameters()
      Return the number of parameters (coefficients) in the linear model
      Returns:
      the number of parameters
    • coefficients

      public double[] coefficients()
      Return the array of coefficients
      Returns:
      the coefficients
    • intercept

      public double intercept()
      Return the intercept
      Returns:
      the intercept
    • toString

      public String toString()
      Returns a textual description of this linear model
      Overrides:
      toString in class Object
      Returns:
      String containing a description of this linear model
    • getRevision

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