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## weka.core
Class AbstractStringDistanceFunction

    java.lang.Object
      weka.core.NormalizableDistance
          weka.core.AbstractStringDistanceFunction

All Implemented Interfaces:
  java.io.Serializable, DistanceFunction, OptionHandler, RevisionHandler

Direct Known Subclasses:
  EditDistance

    public abstract class AbstractStringDistanceFunction

extends NormalizableDistance

Represents the abstract ancestor for string-based distance functions, like EditDistance.

Version:
  $Revision: 1.1 $
Author:
  Bruno Woltzenlogel Paleo
See Also:
  Serialized Form

Field Summary

Fields inherited from class weka.core.NormalizableDistance
`R_MAX, R_MIN, R_WIDTH`

Constructor Summary
`AbstractStringDistanceFunction()` Constructor that doesn't set the data
`AbstractStringDistanceFunction(Instances data)` Constructor that sets the data

Method Summary
`double` | `distance(Instance first, Instance second, double cutOffValue, PerformanceStats stats)` Calculates the distance between two instances.

Methods inherited from class weka.core.NormalizableDistance
`attributeIndicesTipText, distance, distance, distance, dontNormalizeTipText, getAttributeIndices, getDontNormalize, getInstances, getInvertSelection, getOptions, getRanges, globalInfo, initializeRanges, initializeRanges, initializeRanges, initializeRangesEmpty, inRanges, invertSelectionTipText, listOptions, postProcessDistances, rangesSet, setAttributeIndices, setDontNormalize, setInstances, setInvertSelection, setOptions, toString, update, updateRanges, updateRanges, updateRanges, updateRangesFirst`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Methods inherited from interface weka.core.RevisionHandler
`getRevision`

Constructor Detail

### AbstractStringDistanceFunction

    public AbstractStringDistanceFunction()

  Constructor that doesn't set the data

### AbstractStringDistanceFunction

    public AbstractStringDistanceFunction(Instances data)

  Constructor that sets the data

  Parameters:
    `data` - the set of instances that will be used for later distance comparisons

Method Detail

### distance

    public double distance(Instance first,
                           Instance second,
                           double cutOffValue,
                           PerformanceStats stats)

  Calculates the distance between two instances. Offers speed up (if the distance function class in use supports it) in nearest neighbour search by taking into account the cutOff or maximum distance. Depending on the distance function class, post processing of the distances by postProcessDistances(double []) may be required if this function is used.

  Specified by:
    `distance` in interface `DistanceFunction`
  Overrides:
    `distance` in class `NormalizableDistance`
  Parameters:
    `first` - the first instance
    `second` - the second instance
    `cutOffValue` - If the distance being calculated becomes larger than cutOffValue then the rest of the calculation is discarded.
    `stats` - the performance stats object
  Returns:
    the distance between the two given instances or Double.POSITIVE_INFINITY if the distance being calculated becomes larger than cutOffValue.

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