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

Constructors

Constructor and Description
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

Modifier and Type	Method and Description
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, clean, 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