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java.lang.Objectweka.filters.Filter
weka.filters.supervised.instance.Resample
public class Resample
Produces a random subsample of a dataset using either sampling with replacement or without replacement.
The original dataset must fit entirely in memory. The number of instances in the generated dataset may be specified. The dataset must have a nominal class attribute. If not, use the unsupervised version. The filter can be made to maintain the class distribution in the subsample, or to bias the class distribution toward a uniform distribution. When used in batch mode (i.e. in the FilteredClassifier), subsequent batches are NOT resampled.
-S <num> Specify the random number seed (default 1)
-Z <num> The size of the output dataset, as a percentage of the input dataset (default 100)
-B <num> Bias factor towards uniform class distribution. 0 = distribution in input data -- 1 = uniform distribution. (default 0)
-no-replacement Disables replacement of instances (default: with replacement)
-V Inverts the selection - only available with '-no-replacement'.
Constructor Summary | |
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Resample()
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Method Summary | |
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boolean |
batchFinished()
Signify that this batch of input to the filter is finished. |
java.lang.String |
biasToUniformClassTipText()
Returns the tip text for this property. |
void |
createSubsampleWithoutReplacement(java.util.Random random,
int origSize,
int sampleSize,
int actualClasses,
int[] classIndices)
creates the subsample without replacement. |
void |
createSubsampleWithReplacement(java.util.Random random,
int origSize,
int sampleSize,
int actualClasses,
int[] classIndices)
creates the subsample with replacement. |
double |
getBiasToUniformClass()
Gets the bias towards a uniform class. |
Capabilities |
getCapabilities()
Returns the Capabilities of this filter. |
boolean |
getInvertSelection()
Gets whether selection is inverted (only if instances are drawn WIHTOUT replacement). |
boolean |
getNoReplacement()
Gets whether instances are drawn with or without replacement. |
java.lang.String[] |
getOptions()
Gets the current settings of the filter. |
int |
getRandomSeed()
Gets the random number seed. |
java.lang.String |
getRevision()
Returns the revision string. |
double |
getSampleSizePercent()
Gets the subsample size as a percentage of the original set. |
java.lang.String |
globalInfo()
Returns a string describing this filter. |
boolean |
input(Instance instance)
Input an instance for filtering. |
java.lang.String |
invertSelectionTipText()
Returns the tip text for this property. |
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 |
noReplacementTipText()
Returns the tip text for this property. |
java.lang.String |
randomSeedTipText()
Returns the tip text for this property. |
java.lang.String |
sampleSizePercentTipText()
Returns the tip text for this property. |
void |
setBiasToUniformClass(double newBiasToUniformClass)
Sets the bias towards a uniform class. |
boolean |
setInputFormat(Instances instanceInfo)
Sets the format of the input instances. |
void |
setInvertSelection(boolean value)
Sets whether the selection is inverted (only if instances are drawn WIHTOUT replacement). |
void |
setNoReplacement(boolean value)
Sets whether instances are drawn with or with out replacement. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setRandomSeed(int newSeed)
Sets the random number seed. |
void |
setSampleSizePercent(double newSampleSizePercent)
Sets the size of the subsample, as a percentage of the original set. |
Methods inherited from class weka.filters.Filter |
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batchFilterFile, filterFile, getCapabilities, getOutputFormat, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, numPendingOutput, output, outputPeek, toString, useFilter, wekaStaticWrapper |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public Resample()
Method Detail |
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public java.lang.String globalInfo()
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-S <num> Specify the random number seed (default 1)
-Z <num> The size of the output dataset, as a percentage of the input dataset (default 100)
-B <num> Bias factor towards uniform class distribution. 0 = distribution in input data -- 1 = uniform distribution. (default 0)
-no-replacement Disables replacement of instances (default: with replacement)
-V Inverts the selection - only available with '-no-replacement'.
setOptions
in interface OptionHandler
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
public java.lang.String biasToUniformClassTipText()
public double getBiasToUniformClass()
public void setBiasToUniformClass(double newBiasToUniformClass)
newBiasToUniformClass
- the new bias value, between 0 and 1.public java.lang.String randomSeedTipText()
public int getRandomSeed()
public void setRandomSeed(int newSeed)
newSeed
- the new random number seed.public java.lang.String sampleSizePercentTipText()
public double getSampleSizePercent()
public void setSampleSizePercent(double newSampleSizePercent)
newSampleSizePercent
- the subsample set size, between 0 and 100.public java.lang.String noReplacementTipText()
public boolean getNoReplacement()
public void setNoReplacement(boolean value)
value
- if true then the replacement of instances is disabledpublic java.lang.String invertSelectionTipText()
public boolean getInvertSelection()
m_NoReplacement
public void setInvertSelection(boolean value)
value
- if true then selection is invertedpublic Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class Filter
Capabilities
public boolean setInputFormat(Instances instanceInfo) throws java.lang.Exception
setInputFormat
in class Filter
instanceInfo
- an Instances object containing the input
instance structure (any instances contained in the object are
ignored - only the structure is required).
java.lang.Exception
- if the input format can't be set
successfullypublic boolean input(Instance instance)
input
in class Filter
instance
- the input instance
java.lang.IllegalStateException
- if no input structure has been definedpublic boolean batchFinished()
batchFinished
in class Filter
java.lang.IllegalStateException
- if no input structure has been definedpublic void createSubsampleWithReplacement(java.util.Random random, int origSize, int sampleSize, int actualClasses, int[] classIndices)
random
- the random number generator to useorigSize
- the original size of the datasetsampleSize
- the size to generateactualClasses
- the number of classes found in the dataclassIndices
- the indices where classes startpublic void createSubsampleWithoutReplacement(java.util.Random random, int origSize, int sampleSize, int actualClasses, int[] classIndices)
random
- the random number generator to useorigSize
- the original size of the datasetsampleSize
- the size to generateactualClasses
- the number of classes found in the dataclassIndices
- the indices where classes startpublic java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Filter
public static void main(java.lang.String[] argv)
argv
- should contain arguments to the filter:
use -h for help
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