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## weka.core
Class ManhattanDistance

    java.lang.Object
      weka.core.NormalizableDistance
          weka.core.ManhattanDistance

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

    public class ManhattanDistance

extends NormalizableDistance
implements TechnicalInformationHandler

Implements the Manhattan distance (or Taxicab geometry). The distance between two points is the sum of the (absolute) differences of their coordinates.
For more information, see:
Wikipedia. Taxicab geometry. URL http://en.wikipedia.org/wiki/Taxicab_geometry.

BibTeX:

     @misc{missing_id,
        author = {Wikipedia},
        title = {Taxicab geometry},
        URL = {http://en.wikipedia.org/wiki/Taxicab_geometry}
     }

Valid options are:

     -D
      Turns off the normalization of attribute
      values in distance calculation.

     -R <col1,col2-col4,...>
      Specifies list of columns to used in the calculation of the
      distance. 'first' and 'last' are valid indices.
      (default: first-last)

     -V
      Invert matching sense of column indices.

Version:
  $Revision: 1.2 $
Author:
  Fracpete (fracpete at waikato dot ac dot nz)
See Also:
  Serialized Form

Field Summary

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

Constructor Summary
`ManhattanDistance()` Constructs an Manhattan Distance object, Instances must be still set.
`ManhattanDistance(Instances data)` Constructs an Manhattan Distance object and automatically initializes the ranges.

Method Summary
`java.lang.String` | `getRevision()` Returns the revision string.
`TechnicalInformation` | `getTechnicalInformation()` Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
`java.lang.String` | `globalInfo()` Returns a string describing this object.

Methods inherited from class weka.core.NormalizableDistance
`attributeIndicesTipText, distance, distance, distance, distance, dontNormalizeTipText, getAttributeIndices, getDontNormalize, getInstances, getInvertSelection, getOptions, getRanges, 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`

Constructor Detail

### ManhattanDistance

    public ManhattanDistance()

  Constructs an Manhattan Distance object, Instances must be still set.

### ManhattanDistance

    public ManhattanDistance(Instances data)

  Constructs an Manhattan Distance object and automatically initializes the ranges.

  Parameters:
    `data` - the instances the distance function should work on

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this object.

  Specified by:
    `globalInfo` in class `NormalizableDistance`
  Returns:
    a description of the evaluator suitable for displaying in the explorer/experimenter gui

### getTechnicalInformation

    public TechnicalInformation getTechnicalInformation()

  Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

  Specified by:
    `getTechnicalInformation` in interface `TechnicalInformationHandler`
  Returns:
    the technical information about this class

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Returns:
    the revision

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