mulan.data
Class LabelPowersetStratification

java.lang.Object
  mulan.data.LabelPowersetStratification

All Implemented Interfaces:

Stratification, TechnicalInformationHandler

public class LabelPowersetStratification
extends Object
implements Stratification, TechnicalInformationHandler

Class for stratifying data based on label combinations

Version:

2012.05.08

Author:

Grigorios Tsoumakas

Constructor Summary

LabelPowersetStratification()
Default constructor

LabelPowersetStratification(int aSeed)
Constructor setting the random seed

Method Summary

TechnicalInformation	getTechnicalInformation() Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
MultiLabelInstances[]	stratify(MultiLabelInstances data, int folds) Creates a number of folds via stratified sampling

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

LabelPowersetStratification

public LabelPowersetStratification()

Default constructor

LabelPowersetStratification

public LabelPowersetStratification(int aSeed)

Constructor setting the random seed

Parameters:

aSeed -

Method Detail

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface TechnicalInformationHandler

Returns:

the technical information about this class

stratify

public MultiLabelInstances[] stratify(MultiLabelInstances data,
                                      int folds)

Description copied from interface: Stratification

Creates a number of folds via stratified sampling

Specified by:

stratify in interface Stratification

Parameters:

data - a multi-label dataset

folds - the number of folds to sample

Returns:

an array of multi-label datasets, one for each fold