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Class weka.classifiers.BVDecompose
java.lang.Object
|
+----weka.classifiers.BVDecompose
- public class BVDecompose
- extends java.lang.Object
- implements OptionHandler
Class for performing a Bias-Variance decomposition on any classifier
using the method specified in:
R. Kohavi & D. Wolpert (1996), Bias plus variance decomposition for
zero-one loss functions, in Proc. of the Thirteenth International
Machine Learning Conference (ICML96)
download postscript.
Valid options are:
-D
Turn on debugging output.
-W classname
Specify the full class name of a learner to perform the
decomposition on (required).
-t filename
Set the arff file to use for the decomposition (required).
-T num
Specify the number of instances in the training pool (default 100).
-c num
Specify the index of the class attribute (default last).
-x num
Set the number of train iterations (default 50).
-s num
Set the seed for the dataset randomisation (default 1).
Options after -- are passed to the designated sub-learner.
- Version:
- $Revision: 1.6 $
- Author:
- Len Trigg (trigg@cs.waikato.ac.nz)
BVDecompose()
-
decompose()
- Carry out the bias-variance decomposition
getBias()
- Get the calculated bias squared
getClassifier()
- Gets the name of the classifier being analysed
getClassIndex()
- Get the index (starting from 1) of the attribute used as the class.
getDataFileName()
- Get the name of the data file used for the decomposition
getDebug()
- Gets whether debugging is turned on
getError()
- Get the calculated error rate
getOptions()
- Gets the current settings of the CheckClassifier.
getSeed()
- Gets the random number seed
getSigma()
- Get the calculated sigma squared
getTrainIterations()
- Gets the maximum number of boost iterations
getTrainPoolSize()
- Get the number of instances in the training pool.
getVariance()
- Get the calculated variance
listOptions()
- Returns an enumeration describing the available options
main(String[])
- Test method for this class
setClassifier(Classifier)
- Set the classifiers being analysed
setClassIndex(int)
- Sets index of attribute to discretize on
setDataFileName(String)
- Sets the maximum number of boost iterations
setDebug(boolean)
- Sets debugging mode
setOptions(String[])
- Parses a given list of options.
setSeed(int)
- Sets the random number seed
setTrainIterations(int)
- Sets the maximum number of boost iterations
setTrainPoolSize(int)
- Set the number of instances in the training pool.
toString()
- Returns description of the bias-variance decomposition results.
BVDecompose
public BVDecompose()
listOptions
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options
- 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:
-D
Turn on debugging output.
-W classname
Specify the full class name of a learner to perform the
decomposition on (required).
-t filename
Set the arff file to use for the decomposition (required).
-T num
Specify the number of instances in the training pool (default 100).
-c num
Specify the index of the class attribute (default last).
-x num
Set the number of train iterations (default 50).
-s num
Set the seed for the dataset randomisation (default 1).
Options after -- are passed to the designated sub-learner.
- 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 CheckClassifier.
- Returns:
- an array of strings suitable for passing to setOptions
getTrainPoolSize
public int getTrainPoolSize()
Get the number of instances in the training pool.
- Returns:
- number of instances in the training pool.
setTrainPoolSize
public void setTrainPoolSize(int numTrain)
Set the number of instances in the training pool.
- Parameters:
numTrain
- number of instances in the training pool.
setClassifier
public void setClassifier(Classifier newClassifier)
Set the classifiers being analysed
- Parameters:
newClassifier
- the Classifier to use.
getClassifier
public Classifier getClassifier()
Gets the name of the classifier being analysed
- Returns:
- the classifier being analysed.
setDebug
public void setDebug(boolean debug)
Sets debugging mode
- Parameters:
debug
- true if debug output should be printed
getDebug
public boolean getDebug()
Gets whether debugging is turned on
- Returns:
- true if debugging output is on
setSeed
public void setSeed(int seed)
Sets the random number seed
getSeed
public int getSeed()
Gets the random number seed
- Returns:
- the random number seed
setTrainIterations
public void setTrainIterations(int trainIterations)
Sets the maximum number of boost iterations
getTrainIterations
public int getTrainIterations()
Gets the maximum number of boost iterations
- Returns:
- the maximum number of boost iterations
setDataFileName
public void setDataFileName(java.lang.String dataFileName)
Sets the maximum number of boost iterations
getDataFileName
public java.lang.String getDataFileName()
Get the name of the data file used for the decomposition
- Returns:
- the name of the data file
getClassIndex
public int getClassIndex()
Get the index (starting from 1) of the attribute used as the class.
- Returns:
- the index of the class attribute
setClassIndex
public void setClassIndex(int classIndex)
Sets index of attribute to discretize on
- Parameters:
index
- the index (starting from 1) of the class attribute
getBias
public double getBias()
Get the calculated bias squared
- Returns:
- the bias squared
getVariance
public double getVariance()
Get the calculated variance
- Returns:
- the variance
getSigma
public double getSigma()
Get the calculated sigma squared
- Returns:
- the sigma squared
getError
public double getError()
Get the calculated error rate
- Returns:
- the error rate
decompose
public void decompose() throws java.lang.Exception
Carry out the bias-variance decomposition
- Throws:
- java.lang.Exception - if the decomposition couldn't be carried out
toString
public java.lang.String toString()
Returns description of the bias-variance decomposition results.
- Returns:
- the bias-variance decomposition results as a string
- Overrides:
- toString in class java.lang.Object
main
public static void main(java.lang.String args[])
Test method for this class
- Parameters:
args
- the command line arguments
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