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.
Method Summary |
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 |
GenericRelevantItemsDataSplitter
public GenericRelevantItemsDataSplitter()
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 removedrelevanceThreshold
- 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 predictrelevantItemIDs
- IDs of items considered relevant to that usertrainingUsers
- 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
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