MyMediaLite
3.11
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Most-popular item recommender More...
Public Member Functions | |
override void | AddFeedback (ICollection< Tuple< int, int >> feedback) |
Add positive feedback events and perform incremental training More... | |
virtual bool | CanPredict (int user_id, int item_id) |
Check whether a useful prediction (i.e. not using a fallback/default answer) can be made for a given user-item combination More... | |
Object | Clone () |
create a shallow copy of the object More... | |
override void | LoadModel (string filename) |
Get the model parameters from a file More... | |
MostPopular () | |
Default constructor More... | |
override float | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination More... | |
IList< Tuple< int, float > > | Recommend (int user_id, int n=-1, ICollection< int > ignore_items=null, ICollection< int > candidate_items=null) |
Recommend items for a given user More... | |
virtual System.Collections.Generic.IList< Tuple< int, float > > | Recommend (int user_id, int n=-1, System.Collections.Generic.ICollection< int > ignore_items=null, System.Collections.Generic.ICollection< int > candidate_items=null) |
override void | RemoveFeedback (ICollection< Tuple< int, int >> feedback) |
Remove all feedback events by the given user-item combinations More... | |
override void | RemoveItem (int item_id) |
Remove all feedback by one item More... | |
override void | RemoveUser (int user_id) |
Remove all feedback by one user More... | |
override void | SaveModel (string filename) |
Save the model parameters to a file More... | |
override string | ToString () |
Return a string representation of the recommender More... | |
override void | Train () |
Learn the model parameters of the recommender from the training data More... | |
Protected Member Functions | |
override void | AddItem (int item_id) |
virtual void | AddUser (int user_id) |
Properties | |
bool | ByUser [get, set] |
If true, the popularity of an item is measured by the number of unique users that have accessed it. If false, the popularity is measured by the number of accesses to the item. More... | |
virtual IPosOnlyFeedback | Feedback [get, set] |
the feedback data to be used for training More... | |
int | MaxItemID [get, set] |
Maximum item ID More... | |
int | MaxUserID [get, set] |
Maximum user ID More... | |
bool | UpdateItems [get, set] |
bool | UpdateUsers [get, set] |
Most-popular item recommender
Items are weighted by how often they have been seen in the past.
This method is not personalized.
This recommender supports incremental updates.
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inline |
Default constructor
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inlinevirtual |
Add positive feedback events and perform incremental training
feedback | collection of user id - item id tuples |
Reimplemented from IncrementalItemRecommender.
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inlinevirtualinherited |
Check whether a useful prediction (i.e. not using a fallback/default answer) can be made for a given user-item combination
It is up to the recommender implementor to decide when a prediction is useful, and to document it accordingly.
user_id | the user ID |
item_id | the item ID |
Implements IRecommender.
Reimplemented in ExternalItemRecommender, ExternalRatingPredictor, BiPolarSlopeOne, SlopeOne, Constant, GlobalAverage, UserAverage, ItemAverage, and Random.
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inlineinherited |
create a shallow copy of the object
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inlinevirtual |
Get the model parameters from a file
filename | the name of the file to read from |
Reimplemented from Recommender.
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inlinevirtual |
Predict rating or score for a given user-item combination
user_id | the user ID |
item_id | the item ID |
Implements Recommender.
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inherited |
Recommend items for a given user
user_id | the user ID |
n | the number of items to recommend, -1 for as many as possible |
ignore_items | collection if items that should not be returned; if null, use empty collection |
candidate_items | the candidate items to choose from; if null, use all items |
Implemented in WeightedEnsemble, and Ensemble.
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inlinevirtual |
Remove all feedback events by the given user-item combinations
feedback | collection of user id - item id tuples |
Reimplemented from IncrementalItemRecommender.
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inlinevirtual |
Remove all feedback by one item
item_id | the item ID |
Reimplemented from IncrementalItemRecommender.
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inlinevirtual |
Remove all feedback by one user
user_id | the user ID |
Reimplemented from IncrementalItemRecommender.
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inlinevirtual |
Save the model parameters to a file
filename | the name of the file to write to |
Reimplemented from Recommender.
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inline |
Return a string representation of the recommender
The ToString() method of recommenders should list the class name and all hyperparameters, separated by space characters.
Implements IRecommender.
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inlinevirtual |
Learn the model parameters of the recommender from the training data
Implements Recommender.
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getset |
If true, the popularity of an item is measured by the number of unique users that have accessed it. If false, the popularity is measured by the number of accesses to the item.
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getsetinherited |
the feedback data to be used for training
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getsetinherited |
Maximum item ID
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getsetinherited |
Maximum user ID