SpreadSubsample

java.lang.Object
- weka.filters.Filter
- - weka.filters.supervised.instance.SpreadSubsample

All Implemented Interfaces:

java.io.Serializable, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, Randomizable, RevisionHandler, WeightedAttributesHandler, SupervisedFilter
```
public class SpreadSubsample
extends Filter
implements SupervisedFilter, OptionHandler, Randomizable, WeightedAttributesHandler
```
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: 14508 $

Author:

Stuart Inglis (stuart@reeltwo.com)

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor and Description

SpreadSubsample()

Constructors
Constructor and Description
`SpreadSubsample()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`adjustWeightsTipText()` Returns the tip text for this property
`boolean`	`batchFinished()` Signify that this batch of input to the filter is finished.
`java.lang.String`	`distributionSpreadTipText()` Returns the tip text for this property
`boolean`	`getAdjustWeights()` Returns true if instance weights will be adjusted to maintain total weight per class.
`Capabilities`	`getCapabilities()` Returns the Capabilities of this filter.
`double`	`getDistributionSpread()` Gets the value for the distribution spread
`double`	`getMaxCount()` Gets the value for the max count
`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.
`int`	`getSeed()` Gets the seed for the random number generations
`java.lang.String`	`globalInfo()` Returns a string describing this filter
`boolean`	`input(Instance instance)` Input an instance for filtering.
`java.util.Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.String`	`maxCountTipText()` Returns the tip text for this property
`java.lang.String`	`randomSeedTipText()` Returns the tip text for this property
`void`	`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 spread
`boolean`	`setInputFormat(Instances instanceInfo)` Sets the format of the input instances.
`void`	`setMaxCount(double maxcount)` Sets the value for the max count
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`void`	`setRandomSeed(int newSeed)` Sets the random number seed.
`void`	`setSeed(int seed)` Set the seed for random number generation.

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

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Constructor Detail
  - SpreadSubsample
```
public SpreadSubsample()
```
- Method Detail
  - 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
  - adjustWeightsTipText
```
public java.lang.String adjustWeightsTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - 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.
  - 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
  - listOptions
```
public java.util.Enumeration<Option> listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class Filter
    
    Returns:
    
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(java.lang.String[] options)
                throws java.lang.Exception
```
    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 interface OptionHandler
    
    Overrides:
    
    setOptions in class Filter
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - getOptions
```
public java.lang.String[] getOptions()
```
    Gets the current settings of the filter.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class Filter
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - distributionSpreadTipText
```
public java.lang.String distributionSpreadTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setDistributionSpread
```
public void setDistributionSpread(double spread)
```
    Sets the value for the distribution spread
    
    Parameters:
    
    spread - the new distribution spread
  - getDistributionSpread
```
public double getDistributionSpread()
```
    Gets the value for the distribution spread
    
    Returns:
    
    the distribution spread
  - maxCountTipText
```
public java.lang.String maxCountTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setMaxCount
```
public void setMaxCount(double maxcount)
```
    Sets the value for the max count
    
    Parameters:
    
    maxcount - the new max count
  - getMaxCount
```
public double getMaxCount()
```
    Gets the value for the max count
    
    Returns:
    
    the max count
  - 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
  - getRandomSeed
```
public int getRandomSeed()
```
    Gets the random number seed.
    
    Returns:
    
    the random number seed.
  - setRandomSeed
```
public void setRandomSeed(int newSeed)
```
    Sets the random number seed.
    
    Parameters:
    
    newSeed - the new random number seed.
  - setSeed
```
@ProgrammaticProperty
public void setSeed(int seed)
```
    Description copied from interface: Randomizable
    
    Set the seed for random number generation.
    
    Specified by:
    
    setSeed in interface Randomizable
    
    Parameters:
    
    seed - the seed
  - getSeed
```
@ProgrammaticProperty
public int getSeed()
```
    Description copied from interface: Randomizable
    
    Gets the seed for the random number generations
    
    Specified by:
    
    getSeed in interface Randomizable
    
    Returns:
    
    the seed for the random number generation
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns the Capabilities of this filter.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Filter
    
    Returns:
    
    the capabilities of this object
    
    See Also:
    
    Capabilities
  - setInputFormat
```
public boolean setInputFormat(Instances instanceInfo)
                       throws java.lang.Exception
```
    Sets the format of the input instances.
    
    Overrides:
    
    setInputFormat in class Filter
    
    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.
    
    java.lang.Exception - if the inputFormat can't be set successfully
  - input
```
public boolean input(Instance instance)
```
    Input an instance for filtering. Filter requires all training instances be read before producing output.
    
    Overrides:
    
    input in class Filter
    
    Parameters:
    
    instance - the input instance
    
    Returns:
    
    true if the filtered instance may now be collected with output().
    
    Throws:
    
    java.lang.IllegalStateException - if no input structure has been defined
  - 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 class Filter
    
    Returns:
    
    true if there are instances pending output
    
    Throws:
    
    java.lang.IllegalStateException - if no input structure has been defined
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Filter
    
    Returns:
    
    the revision
  - 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

Class SpreadSubsample

Constructor Summary

Method Summary

Methods inherited from class weka.filters.Filter

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

SpreadSubsample

Method Detail

globalInfo

adjustWeightsTipText

getAdjustWeights

setAdjustWeights

listOptions

setOptions

getOptions

distributionSpreadTipText

setDistributionSpread

getDistributionSpread

maxCountTipText

setMaxCount

getMaxCount

randomSeedTipText

getRandomSeed

setRandomSeed

setSeed

getSeed

getCapabilities

setInputFormat

input

batchFinished

getRevision

main