Package weka.gui.boundaryvisualizer

Class KDDataGenerator

java.lang.Object
weka.gui.boundaryvisualizer.KDDataGenerator
All Implemented Interfaces:
Serializable, DataGenerator
public class KDDataGenerator extends Object implements DataGenerator, Serializable
KDDataGenerator. Class that uses kernels to generate new random instances based on a supplied set of instances.
Since:
1.0
Version:
$Revision: 10222 $
Author:
Mark Hall
See Also:

  • Constructor Details

    • KDDataGenerator

      public KDDataGenerator()

  • Method Details

    • buildGenerator

      public void buildGenerator(Instances inputInstances) throws Exception
      Initialize the generator using the supplied instances
      Specified by:
      buildGenerator in interface DataGenerator
      Parameters:
      inputInstances - the instances to use as the basis of the kernels
      Throws:
      Exception - if an error occurs

    • getWeights

      public double[] getWeights()
      Description copied from interface: DataGenerator
      Get weights
      Specified by:
      getWeights in interface DataGenerator

    • generateInstances

      public double[][] generateInstances(int[] indices) throws Exception
      Generates a new instance using one kernel estimator. Each successive call to this method incremets the index of the kernel to use.
      Specified by:
      generateInstances in interface DataGenerator
      Returns:
      the new random instance
      Throws:
      Exception - if an error occurs

    • setWeightingDimensions

      public void setWeightingDimensions(boolean[] dims)
      Set which dimensions to use when computing a weight for the next instance to generate
      Specified by:
      setWeightingDimensions in interface DataGenerator
      Parameters:
      dims - an array of booleans indicating which dimensions to use

    • setWeightingValues

      public void setWeightingValues(double[] vals)
      Set the values for the weighting dimensions to be used when computing the weight for the next instance to be generated
      Specified by:
      setWeightingValues in interface DataGenerator
      Parameters:
      vals - an array of doubles containing the values of the weighting dimensions (corresponding to the entries that are set to true throw setWeightingDimensions)

    • getNumGeneratingModels

      public int getNumGeneratingModels()
      Return the number of kernels (there is one per training instance)
      Specified by:
      getNumGeneratingModels in interface DataGenerator
      Returns:
      the number of kernels

    • setKernelBandwidth

      public void setKernelBandwidth(int kb)
      Set the kernel bandwidth (number of nearest neighbours to cover)
      Parameters:
      kb - an int value

    • getKernelBandwidth

      public int getKernelBandwidth()
      Get the kernel bandwidth
      Returns:
      an int value

    • setSeed

      public void setSeed(int seed)
      Initializes a new random number generator using the supplied seed.
      Specified by:
      setSeed in interface DataGenerator
      Parameters:
      seed - an int value