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## weka.filters.supervised.instance
Class SpreadSubsample

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

All Implemented Interfaces:
  java.io.Serializable, CapabilitiesHandler, OptionHandler, RevisionHandler, SupervisedFilter

    public class SpreadSubsample

extends Filter
implements SupervisedFilter, OptionHandler

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: 5492 $
Author:
  Stuart Inglis (stuart@reeltwo.com)
See Also:
  Serialized Form

Constructor Summary
`SpreadSubsample()`

Method Summary
`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.
`java.lang.String` | `globalInfo()` Returns a string describing this filter
`boolean` | `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` | `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.

Methods inherited from class weka.filters.Filter
`batchFilterFile, filterFile, getCapabilities, getOutputFormat, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, numPendingOutput, output, outputPeek, toString, useFilter, wekaStaticWrapper`

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

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 listOptions()

  Returns an enumeration describing the available options.

  Specified by:
    `listOptions` in interface `OptionHandler`
  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`
  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`
  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.

### 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

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