mulan.data
Class IterativeStratification

java.lang.Object
  mulan.data.IterativeStratification

All Implemented Interfaces:

Stratification, TechnicalInformationHandler

public class IterativeStratification
extends Object
implements Stratification, TechnicalInformationHandler

Class for stratifying data based on the iterative stratification method

Version:

2012.05.08

Author:

Konstantinos Sechidis, Grigorios Tsoumakas

Constructor Summary

IterativeStratification()
Default constructor

IterativeStratification(long seed)
Constructor setting a specific 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

IterativeStratification

public IterativeStratification()

Default constructor

IterativeStratification

public IterativeStratification(long seed)

Constructor setting a specific random seed

Parameters:

seed -

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