MyMediaLite
3.03
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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. | |
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. | |
Object | Clone () |
create a shallow copy of the object | |
override void | LoadModel (string filename) |
Get the model parameters from a file. | |
MostPopular () | |
Default constructor. | |
override float | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination. | |
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. | |
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. | |
override void | RemoveItem (int item_id) |
Remove all feedback by one item. | |
override void | RemoveUser (int user_id) |
Remove all feedback by one user. | |
override void | SaveModel (string filename) |
Save the model parameters to a file. | |
override string | ToString () |
Return a string representation of the recommender. | |
override void | Train () |
Learn the model parameters of the recommender from the training data. | |
Protected Member Functions | |
override void | AddItem (int item_id) |
virtual void | AddUser (int user_id) |
Protected Attributes | |
IList< int > | view_count |
View count. | |
Properties | |
virtual IPosOnlyFeedback | Feedback [get, set] |
the feedback data to be used for training | |
int | MaxItemID [get, set] |
Maximum item ID. | |
int | MaxUserID [get, set] |
Maximum user ID. | |
bool | UpdateItems [get, set] |
true if items shall be updated when doing incremental updates | |
bool | UpdateUsers [get, set] |
true if users shall be updated when doing incremental updates |
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.
MostPopular | ( | ) | [inline] |
Default constructor.
override void AddFeedback | ( | ICollection< Tuple< int, int >> | feedback | ) | [inline, virtual] |
Add positive feedback events and perform incremental training.
feedback | collection of user id - item id tuples |
Reimplemented from IncrementalItemRecommender.
virtual bool CanPredict | ( | int | user_id, |
int | item_id | ||
) | [inline, virtual, inherited] |
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 BiPolarSlopeOne, SlopeOne, Constant, GlobalAverage, UserAverage, ItemAverage, and Random.
Object Clone | ( | ) | [inline, inherited] |
create a shallow copy of the object
override void LoadModel | ( | string | filename | ) | [inline, virtual] |
Get the model parameters from a file.
filename | the name of the file to read from |
Reimplemented from Recommender.
override float Predict | ( | int | user_id, |
int | item_id | ||
) | [inline, virtual] |
Predict rating or score for a given user-item combination.
user_id | the user ID |
item_id | the item ID |
Implements Recommender.
IList<Tuple<int, float> > Recommend | ( | int | user_id, |
int | n = -1 , |
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ICollection< int > | ignore_items = null , |
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ICollection< int > | candidate_items = null |
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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.
override void RemoveFeedback | ( | ICollection< Tuple< int, int >> | feedback | ) | [inline, virtual] |
Remove all feedback events by the given user-item combinations.
feedback | collection of user id - item id tuples |
Reimplemented from IncrementalItemRecommender.
override void RemoveItem | ( | int | item_id | ) | [inline, virtual] |
Remove all feedback by one item.
item_id | the item ID |
Reimplemented from IncrementalItemRecommender.
override void RemoveUser | ( | int | user_id | ) | [inline, virtual] |
Remove all feedback by one user.
user_id | the user ID |
Reimplemented from IncrementalItemRecommender.
override void SaveModel | ( | string | filename | ) | [inline, virtual] |
Save the model parameters to a file.
filename | the name of the file to write to |
Reimplemented from Recommender.
override string ToString | ( | ) | [inline, inherited] |
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.
Reimplemented in BPRMF, BiasedMatrixFactorization, BPRMF_Mapping, SVDPlusPlus, MatrixFactorization, CoClustering, SigmoidCombinedAsymmetricFactorModel, SigmoidItemAsymmetricFactorModel, TimeAwareBaseline, SigmoidUserAsymmetricFactorModel, LatentFeatureLogLinearModel, FactorWiseMatrixFactorization, SigmoidSVDPlusPlus, BPRLinear, UserItemBaseline, BPRMF_ItemMapping, SocialMF, BPRMF_UserMapping, NaiveBayes, KNN, KNN, TimeAwareBaselineWithFrequencies, WRMF, MultiCoreBPRMF, BPRMF_ItemMapping_Optimal, SoftMarginRankingMF, BPRMF_ItemMappingSVR, ItemAttributeSVM, BPRMF_UserMapping_Optimal, BPRMF_ItemMappingKNN, WeightedBPRMF, and Constant.
IList<int> view_count [protected] |
View count.
virtual IPosOnlyFeedback Feedback [get, set, inherited] |
the feedback data to be used for training
int MaxItemID [get, set, inherited] |
Maximum item ID.
int MaxUserID [get, set, inherited] |
Maximum user ID.
bool UpdateItems [get, set, inherited] |
true if items shall be updated when doing incremental updates
Set to false if you do not want any updates to the item model parameters when doing incremental updates.
Implements IIncrementalRecommender.
bool UpdateUsers [get, set, inherited] |
true if users shall be updated when doing incremental updates
Default should be true. Set to false if you do not want any updates to the user model parameters when doing incremental updates.
Implements IIncrementalRecommender.