Class EstimatorUtils

java.lang.Object
weka.estimators.EstimatorUtils
All Implemented Interfaces:
RevisionHandler

public class EstimatorUtils extends Object implements RevisionHandler
Contains static utility functions for Estimators.

Version:
$Revision: 15521 $
Author:
Gabi Schmidberger (gabi@cs.waikato.ac.nz)
  • Constructor Details

    • EstimatorUtils

      public EstimatorUtils()
  • Method Details

    • findMinDistance

      public static double findMinDistance(Instances inst, int attrIndex)
      Find the minimum distance between values. Data is assumed to be sorted based on the given attribute. Missing values are skipped if they are at the beginning or the end of the data.
      Parameters:
      inst - sorted instances, sorted
      attrIndex - index of the attribute, they are sorted after
      Returns:
      the minimal distance
    • getMinMax

      public static int getMinMax(Instances inst, int attrIndex, double[] minMax) throws Exception
      Find the minimum and the maximum of the attribute and return it in the last parameter.
      Parameters:
      inst - instances used to build the estimator
      attrIndex - index of the attribute
      minMax - the array to return minimum and maximum in
      Returns:
      number of not missing values
      Throws:
      Exception - if parameter minMax wasn't initialized properly
    • getInstancesFromClass

      public static Vector<Object> getInstancesFromClass(Instances data, int attrIndex, int classIndex, double classValue, Instances workData)
      Returns a dataset that contains all instances of a certain class value.
      Parameters:
      data - dataset to select the instances from
      attrIndex - index of the relevant attribute
      classIndex - index of the class attribute
      classValue - the relevant class value
      Returns:
      a dataset with only
    • getInstancesFromClass

      public static Instances getInstancesFromClass(Instances data, int classIndex, double classValue)
      Returns a dataset that contains of all instances of a certain class value. Missing values are not dealt with.
      Parameters:
      data - dataset to select the instances from
      classIndex - index of the class attribute
      classValue - the class value
      Returns:
      a dataset with only instances of one class value
    • writeCurve

      public static void writeCurve(String f, Estimator est, double min, double max, int numPoints) throws Exception
      Output of an n points of a density curve. Filename is parameter f + ".curv".
      Parameters:
      f - string to build filename
      est -
      min -
      max -
      numPoints -
      Throws:
      Exception - if something goes wrong
    • writeCurve

      public static void writeCurve(String f, Estimator est, Estimator classEst, double classIndex, double min, double max, int numPoints) throws Exception
      Output of an n points of a density curve. Filename is parameter f + ".curv".
      Parameters:
      f - string to build filename
      est -
      classEst -
      classIndex -
      min -
      max -
      numPoints -
      Throws:
      Exception - if something goes wrong
    • getInstancesFromValue

      public static Instances getInstancesFromValue(Instances data, int index, double v)
      Returns a dataset that contains of all instances of a certain value for the given attribute. Does not deal with missing values.
      Parameters:
      data - dataset to select the instances from
      index - the index of the attribute
      v - the value
      Returns:
      a subdataset with only instances of one value for the attribute
    • cutpointsToString

      public static String cutpointsToString(double[] cutPoints, boolean[] cutAndLeft)
      Returns a string representing the cutpoints.
    • getRevision

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