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Class weka.filters.ResampleFilter 

java.lang.Object
   |
   +----weka.filters.Filter
           |
           +----weka.filters.ResampleFilter
public class ResampleFilter
extends Filter
implements OptionHandler
Produces a random subsample of a dataset. The original dataset must fit entirely in memory. The number of instances in the generated dataset may be specified. If the dataset has a (nominal) class attribute, the filter can be made to maintain the class distribution in the subsample, or to bias the class distribution toward a uniform distribution. Valid options are:

-S num
Specify the random number seed (default 1).

-B num
Specify a bias towards uniform class distribution. 0 = distribution in input data, 1 = uniform class distribution (default 0).

-Z percent
Specify the size of the output dataset, as a percentage of the input dataset (default 100).

Version:
$Revision: 1.2 $
Author:
Len Trigg (len@intelligenesis.net)

Constructor Index

o ResampleFilter()

Method Index

o batchFinished()
Signify that this batch of input to the filter is finished.
o getBiasToUniformClass()
Gets the bias towards a uniform class.
o getOptions()
Gets the current settings of the filter.
o getRandomSeed()
Gets the random number seed.
o getSampleSizePercent()
Gets the subsample size as a percentage of the original set.
o input(Instance)
Input an instance for filtering.
o inputFormat(Instances)
Sets the format of the input instances.
o listOptions()
Returns an enumeration describing the available options
o main(String[])
Main method for testing this class.
o setBiasToUniformClass(double)
Sets the bias towards a uniform class.
o setOptions(String[])
Parses a list of options for this object.
o setRandomSeed(int)
Sets the random number seed.
o setSampleSizePercent(double)
Sets the size of the subsample, as a percentage of the original set.

Constructors

o ResampleFilter 
 public ResampleFilter()

Methods

o listOptions 
 public Enumeration listOptions()
Returns an enumeration describing the available options

Returns:
an enumeration of all the available options
o setOptions 
 public void setOptions(String options[]) throws Exception
Parses a list of options for this object. Valid options are:

-S num
Specify the random number seed (default 1).

-B num
Specify a bias towards uniform class distribution. 0 = distribution in input data, 1 = uniform class distribution (default 0).

-Z percent
Specify the size of the output dataset, as a percentage of the input dataset (default 100).

Parameters:
options - the list of options as an array of strings
Throws: Exception
if an option is not supported
o getOptions 
 public String[] getOptions()
Gets the current settings of the filter.

Returns:
an array of strings suitable for passing to setOptions
o getBiasToUniformClass 
 public double getBiasToUniformClass()
Gets the bias towards a uniform class. A value of 0 leaves the class distribution as-is, a value of 1 ensures the class distributions are uniform in the output data.

Returns:
the current bias
o setBiasToUniformClass 
 public void setBiasToUniformClass(double newBiasToUniformClass)
Sets the bias towards a uniform class. A value of 0 leaves the class distribution as-is, a value of 1 ensures the class distributions are uniform in the output data.

Parameters:
newBiasToUniformClass - the new bias value, between 0 and 1.
o getRandomSeed 
 public int getRandomSeed()
Gets the random number seed.

Returns:
the random number seed.
o setRandomSeed 
 public void setRandomSeed(int newSeed)
Sets the random number seed.

Parameters:
newSeed - the new random number seed.
o getSampleSizePercent 
 public double getSampleSizePercent()
Gets the subsample size as a percentage of the original set.

Returns:
the subsample size
o setSampleSizePercent 
 public void setSampleSizePercent(double newSampleSizePercent)
Sets the size of the subsample, as a percentage of the original set.

Parameters:
newSampleSizePercent - the subsample set size, between 0 and 100.
o inputFormat 
 public boolean inputFormat(Instances instanceInfo) throws Exception
Sets the format of the input instances.

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: Exception
if the input format can't be set successfully
Overrides:
inputFormat in class Filter
o input 
 public boolean input(Instance instance) throws Exception
Input an instance for filtering. Filter requires all training instances be read before producing output.

Parameters:
instance - the input instance
Returns:
true if the filtered instance may now be collected with output().
Throws: Exception
if the input instance was not of the correct format or if there was a problem with the filtering.
Overrides:
input in class Filter
o batchFinished 
 public boolean batchFinished() throws Exception
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.

Returns:
true if there are instances pending output
Throws: Exception
if no input structure has been defined
Overrides:
batchFinished in class Filter
o main 
 public static void main(String argv[])
Main method for testing this class.

Parameters:
argv - should contain arguments to the filter: use -h for help 
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