org.apache.mahout.cf.taste.impl.eval

Class GenericRelevantItemsDataSplitter

java.lang.Object

org.apache.mahout.cf.taste.impl.eval.GenericRelevantItemsDataSplitter

All Implemented Interfaces:

RelevantItemsDataSplitter

public final class GenericRelevantItemsDataSplitter
extends Object
implements RelevantItemsDataSplitter

Picks relevant items to be those with the strongest preference, and includes the other users' preferences in full.

Constructor Summary

Constructors

Constructor and Description
GenericRelevantItemsDataSplitter()

Method Summary

Modifier and Type	Method and Description
FastIDSet	getRelevantItemsIDs(long userID, int at, double relevanceThreshold, DataModel dataModel) During testing, relevant items are removed from a particular users' preferences, and a model is build using this user's other preferences and all other users.
void	processOtherUser(long userID, FastIDSet relevantItemIDs, FastByIDMap<PreferenceArray> trainingUsers, long otherUserID, DataModel dataModel) Adds a single user and all their preferences to the training model.

Methods inherited from class java.lang.Object

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

Constructor Detail

GenericRelevantItemsDataSplitter

public GenericRelevantItemsDataSplitter()

Method Detail

getRelevantItemsIDs

public FastIDSet getRelevantItemsIDs(long userID,
                                     int at,
                                     double relevanceThreshold,
                                     DataModel dataModel)
                              throws TasteException

Description copied from interface: RelevantItemsDataSplitter

During testing, relevant items are removed from a particular users' preferences, and a model is build using this user's other preferences and all other users.

Specified by:

getRelevantItemsIDs in interface RelevantItemsDataSplitter

at - Maximum number of items to be removed

relevanceThreshold - Minimum strength of preference for an item to be considered relevant

Returns:

IDs of relevant items

Throws:

TasteException

processOtherUser

public void processOtherUser(long userID,
                             FastIDSet relevantItemIDs,
                             FastByIDMap<PreferenceArray> trainingUsers,
                             long otherUserID,
                             DataModel dataModel)
                      throws TasteException

Description copied from interface: RelevantItemsDataSplitter

Adds a single user and all their preferences to the training model.

Specified by:

processOtherUser in interface RelevantItemsDataSplitter

Parameters:

userID - ID of user whose preferences we are trying to predict

relevantItemIDs - IDs of items considered relevant to that user

trainingUsers - the database of training preferences to which we will append the ones for otherUserID.

otherUserID - for whom we are adding preferences to the training model

Throws:

TasteException