MyMediaLite
3.04
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Abstract recommender class implementing default behaviors. More...
Public Member Functions | |
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 | |
virtual void | LoadModel (string file) |
Get the model parameters from a file. | |
abstract 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) |
virtual void | SaveModel (string file) |
Save the model parameters to a file. | |
override string | ToString () |
Return a string representation of the recommender. | |
abstract void | Train () |
Learn the model parameters of the recommender from the training data. | |
Properties | |
int | MaxItemID [get, set] |
Maximum item ID. | |
int | MaxUserID [get, set] |
Maximum user ID. |
Abstract recommender class implementing default behaviors.
virtual bool CanPredict | ( | int | user_id, |
int | item_id | ||
) | [inline, virtual] |
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] |
create a shallow copy of the object
virtual void LoadModel | ( | string | filename | ) | [inline, virtual] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements IRecommender.
Reimplemented in BPRMF, MatrixFactorization, BiasedMatrixFactorization, CoClustering, SVDPlusPlus, BPRLinear, UserItemBaseline, FactorWiseMatrixFactorization, SigmoidCombinedAsymmetricFactorModel, SigmoidSVDPlusPlus, BiPolarSlopeOne, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, KNN, MostPopular, NaiveBayes, KNN, SlopeOne, ItemAttributeSVM, MostPopularByAttributes, MF, EntityAverage, GlobalAverage, Constant, Random, Random, and Zero.
abstract float Predict | ( | int | user_id, |
int | item_id | ||
) | [pure virtual] |
Predict rating or score for a given user-item combination.
user_id | the user ID |
item_id | the item ID |
Implements IRecommender.
Implemented in BPRMF, BiasedMatrixFactorization, LatentFeatureLogLinearModel, MatrixFactorization, TimeAwareBaseline, BPRMF_ItemMapping, BPRLinear, BPRMF_UserMapping, FactorWiseMatrixFactorization, UserItemBaseline, CoClustering, NaiveBayes, SVDPlusPlus, ItemAttributeSVM, SigmoidCombinedAsymmetricFactorModel, MF, MostPopularByAttributes, SigmoidSVDPlusPlus, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, MostPopular, BiPolarSlopeOne, ItemKNN, UserKNN, SlopeOne, ItemKNN, Constant, GlobalAverage, UserKNN, UserAverage, ItemAverage, Random, Random, and Zero.
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.
virtual void SaveModel | ( | string | filename | ) | [inline, virtual] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements IRecommender.
Reimplemented in BPRMF, MatrixFactorization, BiasedMatrixFactorization, CoClustering, SVDPlusPlus, BPRLinear, UserItemBaseline, FactorWiseMatrixFactorization, BiPolarSlopeOne, SigmoidCombinedAsymmetricFactorModel, NaiveBayes, SigmoidItemAsymmetricFactorModel, SigmoidUserAsymmetricFactorModel, SlopeOne, KNN, MostPopular, KNN, ItemAttributeSVM, MostPopularByAttributes, MF, EntityAverage, GlobalAverage, Constant, Random, Random, and Zero.
override string ToString | ( | ) | [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.
Reimplemented in BPRMF, BiasedMatrixFactorization, BPRMF_Mapping, SVDPlusPlus, MatrixFactorization, CoClustering, SigmoidCombinedAsymmetricFactorModel, SigmoidItemAsymmetricFactorModel, TimeAwareBaseline, SigmoidUserAsymmetricFactorModel, LatentFeatureLogLinearModel, FactorWiseMatrixFactorization, UserItemBaseline, BPRLinear, SigmoidSVDPlusPlus, BPRMF_ItemMapping, SocialMF, BPRMF_UserMapping, NaiveBayes, KNN, KNN, MostPopular, TimeAwareBaselineWithFrequencies, WRMF, MultiCoreBPRMF, BPRMF_ItemMapping_Optimal, CLiMF, SoftMarginRankingMF, BPRMF_ItemMappingSVR, ItemAttributeSVM, BPRMF_UserMapping_Optimal, BPRMF_ItemMappingKNN, WeightedBPRMF, and Constant.
int MaxItemID [get, set] |
Maximum item ID.
int MaxUserID [get, set] |
Maximum user ID.