IRatingPredictor Interface Reference

interface for rating predictors More...

Inheritance diagram for IRatingPredictor:
IRecommender RatingPredictor BiPolarSlopeOne EntityAverage GlobalAverage MatrixFactorization SlopeOne UserItemBaseline ItemAverage UserAverage BiasedMatrixFactorization KNN ItemKNN UserKNN ItemAttributeKNN ItemKNNCosine ItemKNNPearson UserAttributeKNN UserKNNCosine UserKNNPearson

List of all members.

Public Member Functions

void Add (int user_id, int item_id, double rating)
void AddItem (int item_id)
void AddUser (int user_id)
bool CanPredict (int user_id, int item_id)
 Check whether a useful prediction can be made for a given user-item combination.
void LoadModel (string filename)
 Get the model parameters from a file.
double Predict (int user_id, int item_id)
 Predict rating or score for a given user-item combination.
void RemoveItem (int item_id)
void RemoveRating (int user_id, int item_id)
void RemoveUser (int user_id)
void SaveModel (string filename)
 Save the model parameters to a file.
string ToString ()
 Return a string representation of the recommender.
void Train ()
 Learn the model parameters of the recommender from the training data.
void UpdateRating (int user_id, int item_id, double rating)

Properties

double MaxRating [get, set]
 The max rating value.
double MinRating [get, set]
 The min rating value.

Detailed Description

interface for rating predictors


Member Function Documentation

bool CanPredict ( int  user_id,
int  item_id 
) [inherited]

Check whether a useful prediction can be made for a given user-item combination.

Parameters:
user_id the user ID
item_id the item ID
Returns:
true if a useful prediction can be made, false otherwise

Implemented in Ensemble, ItemRecommender, BiPolarSlopeOne, GlobalAverage, ItemAverage, RatingPredictor, SlopeOne, and UserAverage.

void LoadModel ( string  filename  )  [inherited]

Get the model parameters from a file.

Parameters:
filename the name of the file to read from

Implemented in Ensemble, WeightedEnsemble, BPR_Linear, BPRMF, ItemRecommender, KNN, MF, MostPopular, Random, Zero, BiasedMatrixFactorization, BiPolarSlopeOne, EntityAverage, GlobalAverage, ItemKNN, KNN, MatrixFactorization, RatingPredictor, SlopeOne, and UserItemBaseline.

double Predict ( int  user_id,
int  item_id 
) [inherited]

Predict rating or score for a given user-item combination.

Parameters:
user_id the user ID
item_id the item ID
Returns:
the predicted score/rating for the given user-item combination

Implemented in Ensemble, WeightedEnsemble, BPR_Linear, BPRMF, ItemKNN, ItemRecommender, MF, MostPopular, Random, UserKNN, WeightedItemKNN, WeightedUserKNN, Zero, BiasedMatrixFactorization, BiPolarSlopeOne, GlobalAverage, ItemAverage, ItemKNN, MatrixFactorization, RatingPredictor, SlopeOne, UserAverage, UserItemBaseline, and UserKNN.

void SaveModel ( string  filename  )  [inherited]

Save the model parameters to a file.

Parameters:
filename the name of the file to write to

Implemented in Ensemble, WeightedEnsemble, BPR_Linear, BPRMF, ItemRecommender, KNN, MF, MostPopular, Random, Zero, BiasedMatrixFactorization, BiPolarSlopeOne, EntityAverage, GlobalAverage, KNN, MatrixFactorization, RatingPredictor, SlopeOne, and UserItemBaseline.

string ToString (  )  [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.

Implemented in BPR_Linear, BPRMF, ItemAttributeKNN, ItemKNN, MostPopular, Random, UserAttributeKNN, UserKNN, WeightedItemKNN, WeightedUserKNN, WRMF, Zero, BiasedMatrixFactorization, BiPolarSlopeOne, GlobalAverage, ItemAttributeKNN, ItemAverage, ItemKNNCosine, ItemKNNPearson, MatrixFactorization, SlopeOne, UserAttributeKNN, UserAverage, UserItemBaseline, UserKNNCosine, and UserKNNPearson.


Property Documentation

double MaxRating [get, set]

The max rating value.

Implemented in RatingPredictor.

double MinRating [get, set]

The min rating value.

Implemented in RatingPredictor.


The documentation for this interface was generated from the following file:
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