java.lang.Object
- weka.core.NormalizableDistance

All Implemented Interfaces:

java.io.Serializable, DistanceFunction, OptionHandler, RevisionHandler

Direct Known Subclasses:

AbstractStringDistanceFunction, ChebyshevDistance, EuclideanDistance, ManhattanDistance
```
public abstract class NormalizableDistance
extends java.lang.Object
implements DistanceFunction, OptionHandler, java.io.Serializable, RevisionHandler
```
Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.

Version:

$Revision: 1.2 $

Author:

Fracpete (fracpete at waikato dot ac dot nz), Gabi Schmidberger (gabi@cs.waikato.ac.nz) -- original code from weka.core.EuclideanDistance, Ashraf M. Kibriya (amk14@cs.waikato.ac.nz) -- original code from weka.core.EuclideanDistance

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field Description

static int R_MAX
Index in ranges for MAX.

static int R_MIN
Index in ranges for MIN.

static int R_WIDTH
Index in ranges for WIDTH.

Constructor Summary

Constructors
Constructor	Description
`NormalizableDistance()`	Invalidates the distance function, Instances must be still set.
`NormalizableDistance(Instances data)`	Initializes the distance function and automatically initializes the ranges.

Method Summary

All Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method	Description
`java.lang.String`	`attributeIndicesTipText()`	Returns the tip text for this property.
`void`	`clean()`	Free any references to training instances
`double`	`distance(Instance first, Instance second)`	Calculates the distance between two instances.
`double`	`distance(Instance first, Instance second, double cutOffValue)`	Calculates the distance between two instances.
`double`	`distance(Instance first, Instance second, double cutOffValue, PerformanceStats stats)`	Calculates the distance between two instances.
`double`	`distance(Instance first, Instance second, PerformanceStats stats)`	Calculates the distance between two instances.
`java.lang.String`	`dontNormalizeTipText()`	Returns the tip text for this property.
`java.lang.String`	`getAttributeIndices()`	Gets the range of attributes used in the calculation of the distance.
`boolean`	`getDontNormalize()`	Gets whether if the attribute values are to be normazlied in distance calculation.
`Instances`	`getInstances()`	returns the instances currently set.
`boolean`	`getInvertSelection()`	Gets whether the matching sense of attribute indices is inverted or not.
`java.lang.String[]`	`getOptions()`	Gets the current settings.
`double[][]`	`getRanges()`	Method to get the ranges.
`abstract java.lang.String`	`globalInfo()`	Returns a string describing this object.
`double[][]`	`initializeRanges()`	Initializes the ranges using all instances of the dataset.
`double[][]`	`initializeRanges(int[] instList)`	Initializes the ranges of a subset of the instances of this dataset.
`double[][]`	`initializeRanges(int[] instList, int startIdx, int endIdx)`	Initializes the ranges of a subset of the instances of this dataset.
`void`	`initializeRangesEmpty(int numAtt, double[][] ranges)`	Used to initialize the ranges.
`boolean`	`inRanges(Instance instance, double[][] ranges)`	Test if an instance is within the given ranges.
`java.lang.String`	`invertSelectionTipText()`	Returns the tip text for this property.
`java.util.Enumeration`	`listOptions()`	Returns an enumeration describing the available options.
`void`	`postProcessDistances(double[] distances)`	Does nothing, derived classes may override it though.
`boolean`	`rangesSet()`	Check if ranges are set.
`void`	`setAttributeIndices(java.lang.String value)`	Sets the range of attributes to use in the calculation of the distance.
`void`	`setDontNormalize(boolean dontNormalize)`	Sets whether if the attribute values are to be normalized in distance calculation.
`void`	`setInstances(Instances insts)`	Sets the instances.
`void`	`setInvertSelection(boolean value)`	Sets whether the matching sense of attribute indices is inverted or not.
`void`	`setOptions(java.lang.String[] options)`	Parses a given list of options.
`java.lang.String`	`toString()`	Returns an empty string.
`void`	`update(Instance ins)`	Update the distance function (if necessary) for the newly added instance.
`void`	`updateRanges(Instance instance)`	Update the ranges if a new instance comes.
`double[][]`	`updateRanges(Instance instance, double[][] ranges)`	Updates the ranges given a new instance.
`void`	`updateRanges(Instance instance, int numAtt, double[][] ranges)`	Updates the minimum and maximum and width values for all the attributes based on a new instance.
`void`	`updateRangesFirst(Instance instance, int numAtt, double[][] ranges)`	Used to initialize the ranges.

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

Methods inherited from interface weka.core.RevisionHandler
getRevision

- Field Detail
  - R_MIN
```
public static final int R_MIN
```
    Index in ranges for MIN.
    
    See Also:
    
    Constant Field Values
  - R_MAX
```
public static final int R_MAX
```
    Index in ranges for MAX.
    
    See Also:
    
    Constant Field Values
  - R_WIDTH
```
public static final int R_WIDTH
```
    Index in ranges for WIDTH.
    
    See Also:
    
    Constant Field Values
- Constructor Detail
  - NormalizableDistance
```
public NormalizableDistance()
```
    Invalidates the distance function, Instances must be still set.
  - NormalizableDistance
```
public NormalizableDistance(Instances data)
```
    Initializes the distance function and automatically initializes the ranges.
    
    Parameters:
    
    data - the instances the distance function should work on
- Method Detail
  - globalInfo
```
public abstract java.lang.String globalInfo()
```
    Returns a string describing this object.
    
    Returns:
    
    a description of the evaluator suitable for displaying in the explorer/experimenter gui
  - listOptions
```
public java.util.Enumeration listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Returns:
    
    an enumeration of all the available options.
  - getOptions
```
public java.lang.String[] getOptions()
```
    Gets the current settings. Returns empty array.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    
    an array of strings suitable for passing to setOptions()
  - setOptions
```
public void setOptions(java.lang.String[] options)
                throws java.lang.Exception
```
    Parses a given list of options.
    
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - dontNormalizeTipText
```
public java.lang.String dontNormalizeTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setDontNormalize
```
public void setDontNormalize(boolean dontNormalize)
```
    Sets whether if the attribute values are to be normalized in distance calculation.
    
    Parameters:
    
    dontNormalize - if true the values are not normalized
  - getDontNormalize
```
public boolean getDontNormalize()
```
    Gets whether if the attribute values are to be normazlied in distance calculation. (default false i.e. attribute values are normalized.)
    
    Returns:
    
    false if values get normalized
  - attributeIndicesTipText
```
public java.lang.String attributeIndicesTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setAttributeIndices
```
public void setAttributeIndices(java.lang.String value)
```
    Sets the range of attributes to use in the calculation of the distance. The indices start from 1, 'first' and 'last' are valid as well. E.g.: first-3,5,6-last
    
    Specified by:
    
    setAttributeIndices in interface DistanceFunction
    
    Parameters:
    
    value - the new attribute index range
  - getAttributeIndices
```
public java.lang.String getAttributeIndices()
```
    Gets the range of attributes used in the calculation of the distance.
    
    Specified by:
    
    getAttributeIndices in interface DistanceFunction
    
    Returns:
    
    the attribute index range
  - invertSelectionTipText
```
public java.lang.String invertSelectionTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setInvertSelection
```
public void setInvertSelection(boolean value)
```
    Sets whether the matching sense of attribute indices is inverted or not.
    
    Specified by:
    
    setInvertSelection in interface DistanceFunction
    
    Parameters:
    
    value - if true the matching sense is inverted
  - getInvertSelection
```
public boolean getInvertSelection()
```
    Gets whether the matching sense of attribute indices is inverted or not.
    
    Specified by:
    
    getInvertSelection in interface DistanceFunction
    
    Returns:
    
    true if the matching sense is inverted
  - setInstances
```
public void setInstances(Instances insts)
```
    Sets the instances.
    
    Specified by:
    
    setInstances in interface DistanceFunction
    
    Parameters:
    
    insts - the instances to use
  - getInstances
```
public Instances getInstances()
```
    returns the instances currently set.
    
    Specified by:
    
    getInstances in interface DistanceFunction
    
    Returns:
    
    the current instances
  - postProcessDistances
```
public void postProcessDistances(double[] distances)
```
    Does nothing, derived classes may override it though.
    
    Specified by:
    
    postProcessDistances in interface DistanceFunction
    
    Parameters:
    
    distances - the distances to post-process
  - update
```
public void update(Instance ins)
```
    Update the distance function (if necessary) for the newly added instance.
    
    Specified by:
    
    update in interface DistanceFunction
    
    Parameters:
    
    ins - the instance to add
  - distance
```
public double distance(Instance first,
                       Instance second)
```
    Calculates the distance between two instances.
    
    Specified by:
    
    distance in interface DistanceFunction
    
    Parameters:
    
    first - the first instance
    
    second - the second instance
    
    Returns:
    
    the distance between the two given instances
  - distance
```
public double distance(Instance first,
                       Instance second,
                       PerformanceStats stats)
```
    Calculates the distance between two instances.
    
    Specified by:
    
    distance in interface DistanceFunction
    
    Parameters:
    
    first - the first instance
    
    second - the second instance
    
    stats - the performance stats object
    
    Returns:
    
    the distance between the two given instances
  - distance
```
public double distance(Instance first,
                       Instance second,
                       double cutOffValue)
```
    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
    
    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.
    
    Returns:
    
    the distance between the two given instances or Double.POSITIVE_INFINITY if the distance being calculated becomes larger than cutOffValue.
  - 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
    
    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.
  - initializeRanges
```
public double[][] initializeRanges()
```
    Initializes the ranges using all instances of the dataset. Sets m_Ranges.
    
    Returns:
    
    the ranges
  - updateRangesFirst
```
public void updateRangesFirst(Instance instance,
                              int numAtt,
                              double[][] ranges)
```
    Used to initialize the ranges. For this the values of the first instance is used to save time. Sets low and high to the values of the first instance and width to zero.
    
    Parameters:
    
    instance - the new instance
    
    numAtt - number of attributes in the model
    
    ranges - low, high and width values for all attributes
  - updateRanges
```
public void updateRanges(Instance instance,
                         int numAtt,
                         double[][] ranges)
```
    Updates the minimum and maximum and width values for all the attributes based on a new instance.
    
    Parameters:
    
    instance - the new instance
    
    numAtt - number of attributes in the model
    
    ranges - low, high and width values for all attributes
  - initializeRangesEmpty
```
public void initializeRangesEmpty(int numAtt,
                                  double[][] ranges)
```
    Used to initialize the ranges.
    
    Parameters:
    
    numAtt - number of attributes in the model
    
    ranges - low, high and width values for all attributes
  - updateRanges
```
public double[][] updateRanges(Instance instance,
                               double[][] ranges)
```
    Updates the ranges given a new instance.
    
    Parameters:
    
    instance - the new instance
    
    ranges - low, high and width values for all attributes
    
    Returns:
    
    the updated ranges
  - initializeRanges
```
public double[][] initializeRanges(int[] instList)
                            throws java.lang.Exception
```
    Initializes the ranges of a subset of the instances of this dataset. Therefore m_Ranges is not set.
    
    Parameters:
    
    instList - list of indexes of the subset
    
    Returns:
    
    the ranges
    
    Throws:
    
    java.lang.Exception - if something goes wrong
  - initializeRanges
```
public double[][] initializeRanges(int[] instList,
                                   int startIdx,
                                   int endIdx)
                            throws java.lang.Exception
```
    Initializes the ranges of a subset of the instances of this dataset. Therefore m_Ranges is not set. The caller of this method should ensure that the supplied start and end indices are valid (start <= end, end<instList.length etc) and correct.
    
    Parameters:
    
    instList - list of indexes of the instances
    
    startIdx - start index of the subset of instances in the indices array
    
    endIdx - end index of the subset of instances in the indices array
    
    Returns:
    
    the ranges
    
    Throws:
    
    java.lang.Exception - if something goes wrong
  - updateRanges
```
public void updateRanges(Instance instance)
```
    Update the ranges if a new instance comes.
    
    Parameters:
    
    instance - the new instance
  - inRanges
```
public boolean inRanges(Instance instance,
                        double[][] ranges)
```
    Test if an instance is within the given ranges.
    
    Parameters:
    
    instance - the instance
    
    ranges - the ranges the instance is tested to be in
    
    Returns:
    
    true if instance is within the ranges
  - clean
```
public void clean()
```
    Free any references to training instances
    
    Specified by:
    
    clean in interface DistanceFunction
  - rangesSet
```
public boolean rangesSet()
```
    Check if ranges are set.
    
    Returns:
    
    true if ranges are set
  - getRanges
```
public double[][] getRanges()
                     throws java.lang.Exception
```
    Method to get the ranges.
    
    Returns:
    
    the ranges
    
    Throws:
    
    java.lang.Exception - if no randes are set yet
  - toString
```
public java.lang.String toString()
```
    Returns an empty string.
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    an empty string

Modifier and Type	Field	Description
`static int`	`R_MAX`	Index in ranges for MAX.
`static int`	`R_MIN`	Index in ranges for MIN.
`static int`	`R_WIDTH`	Index in ranges for WIDTH.

Class NormalizableDistance

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.RevisionHandler

Field Detail

R_MIN

R_MAX

R_WIDTH

Constructor Detail

NormalizableDistance

NormalizableDistance

Method Detail

globalInfo

listOptions

getOptions

setOptions

dontNormalizeTipText

setDontNormalize

getDontNormalize

attributeIndicesTipText

setAttributeIndices

getAttributeIndices

invertSelectionTipText

setInvertSelection

getInvertSelection

setInstances

getInstances

postProcessDistances

update

distance

distance

distance

distance

initializeRanges

updateRangesFirst

updateRanges

initializeRangesEmpty

updateRanges

initializeRanges

initializeRanges

updateRanges

inRanges

clean

rangesSet

getRanges

toString