weka.core

Class AbstractStringDistanceFunction

java.lang.Object

weka.core.NormalizableDistance

weka.core.AbstractStringDistanceFunction

All Implemented Interfaces:

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

m_ActiveIndices, m_AttributeIndices, m_Data, m_DontNormalize, m_Ranges, m_Validated, R_MAX, R_MIN, R_WIDTH

Constructor Summary

Constructors

Constructor and Description
AbstractStringDistanceFunction() Constructor that doesn't set the data
AbstractStringDistanceFunction(Instances data) Constructor that sets the data

Method Summary

Modifier and Type	Method and Description
protected double	difference(int index, String string1, String string2) Computes the difference between two given attribute values.
double	distance(Instance first, Instance second, double cutOffValue, PerformanceStats stats) Calculates the distance between two instances.
protected double	updateDistance(double currDist, double diff) Updates the current distance calculated so far with the new difference between two attributes.

Methods inherited from class weka.core.NormalizableDistance

attributeIndicesTipText, difference, distance, distance, distance, dontNormalizeTipText, getAttributeIndices, getDontNormalize, getInstances, getInvertSelection, getOptions, getRanges, globalInfo, initialize, initializeAttributeIndices, initializeRanges, initializeRanges, initializeRanges, initializeRangesEmpty, inRanges, invalidate, invertSelectionTipText, listOptions, norm, postProcessDistances, rangesSet, setAttributeIndices, setDontNormalize, setInstances, setInvertSelection, setOptions, toString, update, updateRanges, updateRanges, updateRanges, updateRangesFirst, validate

Methods inherited from class java.lang.Object

clone, equals, finalize, 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

updateDistance

protected double updateDistance(double currDist,
                                double diff)

Updates the current distance calculated so far with the new difference between two attributes. The difference between the attributes was calculated with the difference(int,double,double) method.

Specified by:

updateDistance in class NormalizableDistance

Parameters:

currDist - the current distance calculated so far

diff - the difference between two new attributes

Returns:

the update distance

See Also:

NormalizableDistance.difference(int, double, double)

difference

protected double difference(int index,
                            String string1,
                            String string2)

Computes the difference between two given attribute values.

Parameters:

index - the attribute index

val1 - the first value

val2 - the second value

Returns:

the difference

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.