Class RandomProjection
- java.lang.Object
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- weka.filters.Filter
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- weka.filters.unsupervised.attribute.RandomProjection
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- All Implemented Interfaces:
java.io.Serializable
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
,UnsupervisedFilter
public class RandomProjection extends Filter implements UnsupervisedFilter, OptionHandler, TechnicalInformationHandler
Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length (i.e. It will reduce the number of attributes in the data while preserving much of its variation like PCA, but at a much less computational cost).
It first applies the NominalToBinary filter to convert all attributes to numeric before reducing the dimension. It preserves the class attribute.
For more information, see:
Dmitriy Fradkin, David Madigan: Experiments with random projections for machine learning. In: KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, New York, NY, USA, 517-522, 003. BibTeX:@inproceedings{Fradkin003, address = {New York, NY, USA}, author = {Dmitriy Fradkin and David Madigan}, booktitle = {KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining}, pages = {517-522}, publisher = {ACM Press}, title = {Experiments with random projections for machine learning}, year = {003} }
Valid options are:-N <number> The number of dimensions (attributes) the data should be reduced to (default 10; exclusive of the class attribute, if it is set).
-D [SPARSE1|SPARSE2|GAUSSIAN] The distribution to use for calculating the random matrix. Sparse1 is: sqrt(3)*{-1 with prob(1/6), 0 with prob(2/3), +1 with prob(1/6)} Sparse2 is: {-1 with prob(1/2), +1 with prob(1/2)}
-P <percent> The percentage of dimensions (attributes) the data should be reduced to (exclusive of the class attribute, if it is set). This -N option is ignored if this option is present and is greater than zero.
-M Replace missing values using the ReplaceMissingValues filter
-R <num> The random seed for the random number generator used for calculating the random matrix (default 42).
- Version:
- $Revision: 10832 $ [1.0 - 22 July 2003 - Initial version (Ashraf M. Kibriya)]
- Author:
- Ashraf M. Kibriya (amk14@cs.waikato.ac.nz)
- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field Description static int
GAUSSIAN
distribution type: gaussianstatic int
SPARSE1
distribution type: sparse 1static int
SPARSE2
distribution type: sparse 2static Tag[]
TAGS_DSTRS_TYPE
The types of distributions that can be used for calculating the random matrix
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Constructor Summary
Constructors Constructor Description RandomProjection()
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description boolean
batchFinished()
Signify that this batch of input to the filter is finished.java.lang.String
distributionTipText()
Returns the tip text for this propertyCapabilities
getCapabilities()
Returns the Capabilities of this filter.SelectedTag
getDistribution()
Returns the current distribution that'll be used for calculating the random matrixint
getNumberOfAttributes()
Gets the current number of attributes (dimensionality) to which the data will be reduced to.java.lang.String[]
getOptions()
Gets the current settings of the filter.double
getPercent()
Gets the percent the attributes (dimensions) of the data will be reduced tolong
getRandomSeed()
Gets the random seed of the random number generatorboolean
getReplaceMissingValues()
Gets the current setting for using ReplaceMissingValues filterjava.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 filterboolean
input(Instance instance)
Input an instance for filtering.java.util.Enumeration
listOptions()
Returns an enumeration describing the available options.static void
main(java.lang.String[] argv)
Main method for testing this class.java.lang.String
numberOfAttributesTipText()
Returns the tip text for this propertyjava.lang.String
percentTipText()
Returns the tip text for this propertyjava.lang.String
randomSeedTipText()
Returns the tip text for this propertyjava.lang.String
replaceMissingValuesTipText()
Returns the tip text for this propertyvoid
setDistribution(SelectedTag newDstr)
Sets the distribution to use for calculating the random matrixboolean
setInputFormat(Instances instanceInfo)
Sets the format of the input instances.void
setNumberOfAttributes(int newAttNum)
Sets the number of attributes (dimensions) the data should be reduced tovoid
setOptions(java.lang.String[] options)
Parses a given list of options.void
setPercent(double newPercent)
Sets the percent the attributes (dimensions) of the data should be reduced tovoid
setRandomSeed(long seed)
Sets the random seed of the random number generatorvoid
setReplaceMissingValues(boolean t)
Sets either to use replace missing values filter or not-
Methods inherited from class weka.filters.Filter
batchFilterFile, filterFile, getCapabilities, getOutputFormat, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, numPendingOutput, output, outputPeek, toString, useFilter, wekaStaticWrapper
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Field Detail
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SPARSE1
public static final int SPARSE1
distribution type: sparse 1- See Also:
- Constant Field Values
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SPARSE2
public static final int SPARSE2
distribution type: sparse 2- See Also:
- Constant Field Values
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GAUSSIAN
public static final int GAUSSIAN
distribution type: gaussian- See Also:
- Constant Field Values
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TAGS_DSTRS_TYPE
public static final Tag[] TAGS_DSTRS_TYPE
The types of distributions that can be used for calculating the random matrix
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Method Detail
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listOptions
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Returns:
- an enumeration of all the available options.
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setOptions
public void setOptions(java.lang.String[] options) throws java.lang.Exception
Parses a given list of options. Valid options are:-N <number> The number of dimensions (attributes) the data should be reduced to (default 10; exclusive of the class attribute, if it is set).
-D [SPARSE1|SPARSE2|GAUSSIAN] The distribution to use for calculating the random matrix. Sparse1 is: sqrt(3)*{-1 with prob(1/6), 0 with prob(2/3), +1 with prob(1/6)} Sparse2 is: {-1 with prob(1/2), +1 with prob(1/2)}
-P <percent> The percentage of dimensions (attributes) the data should be reduced to (exclusive of the class attribute, if it is set). This -N option is ignored if this option is present and is greater than zero.
-M Replace missing values using the ReplaceMissingValues filter
-R <num> The random seed for the random number generator used for calculating the random matrix (default 42).
- Specified by:
setOptions
in interfaceOptionHandler
- Parameters:
options
- the list of options as an array of strings- Throws:
java.lang.Exception
- if an option is not supported
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getOptions
public java.lang.String[] getOptions()
Gets the current settings of the filter.- Specified by:
getOptions
in interfaceOptionHandler
- Returns:
- an array of strings suitable for passing to setOptions
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globalInfo
public java.lang.String globalInfo()
Returns a string describing this filter- Returns:
- a description of the filter suitable for displaying in the explorer/experimenter gui
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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 interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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numberOfAttributesTipText
public java.lang.String numberOfAttributesTipText()
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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setNumberOfAttributes
public void setNumberOfAttributes(int newAttNum)
Sets the number of attributes (dimensions) the data should be reduced to- Parameters:
newAttNum
- the goal for the dimensions
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getNumberOfAttributes
public int getNumberOfAttributes()
Gets the current number of attributes (dimensionality) to which the data will be reduced to.- Returns:
- the number of dimensions
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percentTipText
public java.lang.String percentTipText()
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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setPercent
public void setPercent(double newPercent)
Sets the percent the attributes (dimensions) of the data should be reduced to- Parameters:
newPercent
- the percentage of attributes
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getPercent
public double getPercent()
Gets the percent the attributes (dimensions) of the data will be reduced to- Returns:
- the percentage of attributes
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randomSeedTipText
public java.lang.String randomSeedTipText()
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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setRandomSeed
public void setRandomSeed(long seed)
Sets the random seed of the random number generator- Parameters:
seed
- the random seed value
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getRandomSeed
public long getRandomSeed()
Gets the random seed of the random number generator- Returns:
- the random seed value
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distributionTipText
public java.lang.String distributionTipText()
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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setDistribution
public void setDistribution(SelectedTag newDstr)
Sets the distribution to use for calculating the random matrix- Parameters:
newDstr
- the distribution to use
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getDistribution
public SelectedTag getDistribution()
Returns the current distribution that'll be used for calculating the random matrix- Returns:
- the current distribution
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replaceMissingValuesTipText
public java.lang.String replaceMissingValuesTipText()
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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setReplaceMissingValues
public void setReplaceMissingValues(boolean t)
Sets either to use replace missing values filter or not- Parameters:
t
- if true then the replace missing values is used
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getReplaceMissingValues
public boolean getReplaceMissingValues()
Gets the current setting for using ReplaceMissingValues filter- Returns:
- true if the replace missing values filter is used
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getCapabilities
public Capabilities getCapabilities()
Returns the Capabilities of this filter.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classFilter
- Returns:
- the capabilities of this object
- See Also:
Capabilities
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setInputFormat
public boolean setInputFormat(Instances instanceInfo) throws java.lang.Exception
Sets the format of the input instances.- Overrides:
setInputFormat
in classFilter
- Parameters:
instanceInfo
- an Instances object containing the input instance structure (any instances contained in the object are ignored - only the structure is required).- Returns:
- true if the outputFormat may be collected immediately
- Throws:
java.lang.Exception
- if the input format can't be set successfully
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input
public boolean input(Instance instance) throws java.lang.Exception
Input an instance for filtering.- Overrides:
input
in classFilter
- Parameters:
instance
- the input instance- Returns:
- true if the filtered instance may now be collected with output().
- Throws:
java.lang.IllegalStateException
- if no input format has been setjava.lang.NullPointerException
- if the input format has not been defined.java.lang.Exception
- if the input instance was not of the correct format or if there was a problem with the filtering.
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batchFinished
public boolean batchFinished() throws java.lang.Exception
Signify that this batch of input to the filter is finished.- Overrides:
batchFinished
in classFilter
- Returns:
- true if there are instances pending output
- Throws:
java.lang.NullPointerException
- if no input structure has been defined,java.lang.Exception
- if there was a problem finishing the batch.
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classFilter
- Returns:
- the revision
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main
public static void main(java.lang.String[] argv)
Main method for testing this class.- Parameters:
argv
- should contain arguments to the filter: use -h for help
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