Package weka.core
Class MinkowskiDistance
java.lang.Object
weka.core.NormalizableDistance
weka.core.MinkowskiDistance
- All Implemented Interfaces:
Serializable
,Cloneable
,DistanceFunction
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class MinkowskiDistance
extends NormalizableDistance
implements Cloneable, TechnicalInformationHandler
Implementing Minkowski distance (or similarity)
function.
One object defines not one distance but the data model in which the distances between objects of that data model can be computed.
Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.
For more information, see:
Wikipedia. Minkowski distance. URL http://en.wikipedia.org/wiki/Minkowski_distance. BibTeX:
One object defines not one distance but the data model in which the distances between objects of that data model can be computed.
Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.
For more information, see:
Wikipedia. Minkowski distance. URL http://en.wikipedia.org/wiki/Minkowski_distance. BibTeX:
@misc{missing_id, author = {Wikipedia}, title = {Minkowski distance}, URL = {http://en.wikipedia.org/wiki/Minkowski_distance} }Valid options are:
-P <order> The order 'p'. With '1' being the Manhattan distance and '2' the Euclidean distance. (default: 2)
-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: 10203 $
- Author:
- FracPete (fracpete at waikato dot ac dot nz)
- See Also:
-
Field Summary
Fields inherited from class weka.core.NormalizableDistance
R_MAX, R_MIN, R_WIDTH
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Constructor Summary
ConstructorDescriptionConstructs an Minkowski Distance object, Instances must be still set.MinkowskiDistance
(Instances data) Constructs an Minkowski Distance object and automatically initializes the ranges. -
Method Summary
Modifier and TypeMethodDescriptiondouble
Calculates the distance between two instances.double
distance
(Instance first, Instance second, PerformanceStats stats) Calculates the distance (or similarity) between two instances.String[]
Gets the current settings of this object.double
getOrder()
Gets the order.Returns the revision string.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.Returns a string describing this object.Returns an enumeration describing the available options.Returns the tip text for this property.void
postProcessDistances
(double[] distances) Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).void
setOptions
(String[] options) Parses a given list of options.void
setOrder
(double value) Sets the order.Methods inherited from class weka.core.NormalizableDistance
attributeIndicesTipText, clean, distance, distance, dontNormalizeTipText, getAttributeIndices, getDontNormalize, getInstances, getInvertSelection, getRanges, initializeRanges, initializeRanges, initializeRanges, initializeRangesEmpty, inRanges, invertSelectionTipText, rangesSet, setAttributeIndices, setDontNormalize, setInstances, setInvertSelection, toString, update, updateRanges, updateRanges, updateRanges, updateRangesFirst
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Constructor Details
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MinkowskiDistance
public MinkowskiDistance()Constructs an Minkowski Distance object, Instances must be still set. -
MinkowskiDistance
Constructs an Minkowski Distance object and automatically initializes the ranges.- Parameters:
data
- the instances the distance function should work on
-
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Method Details
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globalInfo
Returns a string describing this object.- Specified by:
globalInfo
in classNormalizableDistance
- Returns:
- a description of the evaluator suitable for displaying in the explorer/experimenter gui
-
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 interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
-
listOptions
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classNormalizableDistance
- Returns:
- an enumeration of all the available options.
-
setOptions
Parses a given list of options.- Specified by:
setOptions
in interfaceOptionHandler
- Overrides:
setOptions
in classNormalizableDistance
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
-
getOptions
Gets the current settings of this object.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classNormalizableDistance
- Returns:
- an array of strings suitable for passing to setOptions
-
orderTipText
Returns the tip text for this property.- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setOrder
public void setOrder(double value) Sets the order.- Parameters:
value
- the new order
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getOrder
public double getOrder()Gets the order.- Returns:
- the order
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distance
Calculates the distance between two instances.- Specified by:
distance
in interfaceDistanceFunction
- Overrides:
distance
in classNormalizableDistance
- Parameters:
first
- the first instancesecond
- the second instance- Returns:
- the distance between the two given instances
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distance
Calculates the distance (or similarity) between two instances. Need to pass this returned distance later on to postprocess method to set it on correct scale.
P.S.: Please don't mix the use of this function with distance(Instance first, Instance second), as that already does post processing. Please consider passing Double.POSITIVE_INFINITY as the cutOffValue to this function and then later on do the post processing on all the distances.- Specified by:
distance
in interfaceDistanceFunction
- Overrides:
distance
in classNormalizableDistance
- Parameters:
first
- the first instancesecond
- the second instancestats
- the structure for storing performance statistics.- Returns:
- the distance between the two given instances or Double.POSITIVE_INFINITY.
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postProcessDistances
public void postProcessDistances(double[] distances) Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue). It is necessary to do so to get the correct distances if distance(distance(Instance first, Instance second, double cutOffValue) is used. This is because that function actually returns the squared distance to avoid inaccuracies arising from floating point comparison.- Specified by:
postProcessDistances
in interfaceDistanceFunction
- Overrides:
postProcessDistances
in classNormalizableDistance
- Parameters:
distances
- the distances to post-process
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getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Returns:
- the revision
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