IIterativeModel Interface Reference

Interface representing iteratively trained models. More...

Inheritance diagram for IIterativeModel:
IRecommender BPR_Linear BPRMF MF MatrixFactorization BPRMF WRMF BiasedMatrixFactorization

List of all members.

Public Member Functions

bool CanPredict (int user_id, int item_id)
 Check whether a useful prediction can be made for a given user-item combination.
double ComputeFit ()
 Compute the fit on the training data.
void Iterate ()
 Run one iteration (= pass over the training data).
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 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.

Properties

int NumIter [get, set]

Detailed Description

Interface representing iteratively trained models.


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.

double ComputeFit (  ) 

Compute the fit on the training data.

Returns:
the fit on the training data according to the optimization criterion; -1 if not implemented

Implemented in BPR_Linear, BPRMF, MF, WRMF, and MatrixFactorization.

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

int NumIter [get, set]

Number of iterations to run the training

Implemented in BPR_Linear, MF, and MatrixFactorization.


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