Package weka.filters.supervised.instance
Class SpreadSubsample
java.lang.Object
weka.filters.Filter
weka.filters.supervised.instance.SpreadSubsample
- All Implemented Interfaces:
Serializable
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
,SupervisedFilter
Produces a random subsample of a dataset. The original dataset must fit entirely in memory. This filter allows you to specify the maximum "spread" between the rarest and most common class. For example, you may specify that there be at most a 2:1 difference in class frequencies. When used in batch mode, subsequent batches are NOT resampled.
Valid options are:
-S <num> Specify the random number seed (default 1)
-M <num> The maximum class distribution spread. 0 = no maximum spread, 1 = uniform distribution, 10 = allow at most a 10:1 ratio between the classes (default 0)
-W Adjust weights so that total weight per class is maintained. Individual instance weighting is not preserved. (default no weights adjustment
-X <num> The maximum count for any class value (default 0 = unlimited).
- Version:
- $Revision: 5542 $
- Author:
- Stuart Inglis (stuart@reeltwo.com)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionReturns the tip text for this propertyboolean
Signify that this batch of input to the filter is finished.Returns the tip text for this propertyboolean
Returns true if instance weights will be adjusted to maintain total weight per class.Returns the Capabilities of this filter.double
Gets the value for the distribution spreaddouble
Gets the value for the max countString[]
Gets the current settings of the filter.int
Gets the random number seed.Returns the revision string.Returns a string describing this filterboolean
Input an instance for filtering.Returns an enumeration describing the available options.static void
Main method for testing this class.Returns the tip text for this propertyReturns the tip text for this propertyvoid
setAdjustWeights
(boolean newAdjustWeights) Sets whether the instance weights will be adjusted to maintain total weight per class.void
setDistributionSpread
(double spread) Sets the value for the distribution spreadboolean
setInputFormat
(Instances instanceInfo) Sets the format of the input instances.void
setMaxCount
(double maxcount) Sets the value for the max countvoid
setOptions
(String[] options) Parses a given list of options.void
setRandomSeed
(int newSeed) Sets the random number seed.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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Constructor Details
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SpreadSubsample
public SpreadSubsample()
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Method Details
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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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adjustWeightsTipText
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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getAdjustWeights
public boolean getAdjustWeights()Returns true if instance weights will be adjusted to maintain total weight per class.- Returns:
- true if instance weights will be adjusted to maintain total weight per class.
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setAdjustWeights
public void setAdjustWeights(boolean newAdjustWeights) Sets whether the instance weights will be adjusted to maintain total weight per class.- Parameters:
newAdjustWeights
- whether to adjust weights
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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
Parses a given list of options. Valid options are:-S <num> Specify the random number seed (default 1)
-M <num> The maximum class distribution spread. 0 = no maximum spread, 1 = uniform distribution, 10 = allow at most a 10:1 ratio between the classes (default 0)
-W Adjust weights so that total weight per class is maintained. Individual instance weighting is not preserved. (default no weights adjustment
-X <num> The maximum count for any class value (default 0 = unlimited).
- Specified by:
setOptions
in interfaceOptionHandler
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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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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distributionSpreadTipText
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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setDistributionSpread
public void setDistributionSpread(double spread) Sets the value for the distribution spread- Parameters:
spread
- the new distribution spread
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getDistributionSpread
public double getDistributionSpread()Gets the value for the distribution spread- Returns:
- the distribution spread
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maxCountTipText
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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setMaxCount
public void setMaxCount(double maxcount) Sets the value for the max count- Parameters:
maxcount
- the new max count
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getMaxCount
public double getMaxCount()Gets the value for the max count- Returns:
- the max count
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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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getRandomSeed
public int getRandomSeed()Gets the random number seed.- Returns:
- the random number seed.
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setRandomSeed
public void setRandomSeed(int newSeed) Sets the random number seed.- Parameters:
newSeed
- the new random number seed.
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getCapabilities
Returns the Capabilities of this filter.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classFilter
- Returns:
- the capabilities of this object
- See Also:
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setInputFormat
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:
UnassignedClassException
- if no class attribute has been set.UnsupportedClassTypeException
- if the class attribute is not nominal.Exception
- if the inputFormat can't be set successfully
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input
Input an instance for filtering. Filter requires all training instances be read before producing output.- Overrides:
input
in classFilter
- Parameters:
instance
- the input instance- Returns:
- true if the filtered instance may now be collected with output().
- Throws:
IllegalStateException
- if no input structure has been defined
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batchFinished
public boolean batchFinished()Signify that this batch of input to the filter is finished. If the filter requires all instances prior to filtering, output() may now be called to retrieve the filtered instances.- Overrides:
batchFinished
in classFilter
- Returns:
- true if there are instances pending output
- Throws:
IllegalStateException
- if no input structure has been defined
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getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classFilter
- Returns:
- the revision
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main
Main method for testing this class.- Parameters:
argv
- should contain arguments to the filter: use -h for help
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