net.librec.data.splitter

Class GivenNDataSplitter

java.lang.Object

net.librec.conf.Configured

net.librec.data.splitter.AbstractDataSplitter

net.librec.data.splitter.GivenNDataSplitter

All Implemented Interfaces:

Configurable, DataSplitter

public class GivenNDataSplitter
extends AbstractDataSplitter

GivenN Data Splitter
Split dataset into train set and test set by given number.

Author:

WangYuFeng and liuxz

Nested Class Summary

Nested classes/interfaces inherited from interface net.librec.data.DataSplitter

DataSplitter.SplitterType

Field Summary

Fields inherited from class net.librec.data.splitter.AbstractDataSplitter

dataConvertor, LOG, testMatrix, trainMatrix, validationMatrix

Fields inherited from class net.librec.conf.Configured

conf, CONF_DATA_COLUMN_FORMAT, CONF_DATA_INPUT_PATH, CONF_DFS_DATA_DIR

Constructor Summary

Constructors

Constructor and Description
GivenNDataSplitter() Empty constructor.
GivenNDataSplitter(DataConvertor dataConvertor, Configuration conf) Initializes a newly created GivenNDataSplitter object with configuration.

Method Summary

Methods

Modifier and Type	Method and Description
void	getGivenNByItem(int numGiven) Split ratings into two parts: the training set consisting of user-item ratings where numGiven ratings are preserved for each item, and the rest are used as the testing data.
void	getGivenNByItemDate(int numGiven) Split ratings into two parts: the training set consisting of user-item ratings where numGiven earliest ratings are preserved for each item, and the rest are used as the testing data.
void	getGivenNByUser(int numGiven) Split ratings into two parts: the training set consisting of user-item ratings where numGiven ratings are preserved for each user, and the rest are used as the testing data.
void	getGivenNByUserDate(int numGiven) Split ratings into two parts: the training set consisting of user-item ratings where numGiven earliest ratings are preserved for each user, and the rest are used as the testing data.
void	splitData() Split the data.

Methods inherited from class net.librec.data.splitter.AbstractDataSplitter

getTestData, getTrainData, getValidData, setDataConvertor

Methods inherited from class net.librec.conf.Configured

getConf, setConf

Methods inherited from class java.lang.Object

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

Constructor Detail

GivenNDataSplitter

public GivenNDataSplitter()

Empty constructor.

GivenNDataSplitter

public GivenNDataSplitter(DataConvertor dataConvertor,
                  Configuration conf)

Initializes a newly created GivenNDataSplitter object with configuration.

Parameters:

dataConvertor - data convertor

conf - the configuration for the splitter.

Method Detail

splitData

public void splitData()
               throws LibrecException

Split the data.

Throws:

LibrecException - if error occurs

getGivenNByUser

public void getGivenNByUser(int numGiven)
                     throws java.lang.Exception

Split ratings into two parts: the training set consisting of user-item ratings where numGiven ratings are preserved for each user, and the rest are used as the testing data.

Parameters:

numGiven - given number

Throws:

java.lang.Exception - if error occurs

getGivenNByUserDate

public void getGivenNByUserDate(int numGiven)

Split ratings into two parts: the training set consisting of user-item ratings where numGiven earliest ratings are preserved for each user, and the rest are used as the testing data.

Parameters:

numGiven - given number

getGivenNByItem

public void getGivenNByItem(int numGiven)
                     throws java.lang.Exception

Split ratings into two parts: the training set consisting of user-item ratings where numGiven ratings are preserved for each item, and the rest are used as the testing data.

Parameters:

numGiven - given number

Throws:

java.lang.Exception - if error occurs

getGivenNByItemDate

public void getGivenNByItemDate(int numGiven)

Split ratings into two parts: the training set consisting of user-item ratings where numGiven earliest ratings are preserved for each item, and the rest are used as the testing data.

Parameters:

numGiven - given number