UserAverage Class Reference

Uses the average rating value of a user for predictions. More...

Inheritance diagram for UserAverage:
EntityAverage RatingPredictor IRatingPredictor IRecommender

List of all members.

Public Member Functions

virtual void AddRating (int user_id, int item_id, double rating)
override bool CanPredict (int user_id, int item_id)
 Check whether a useful prediction 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.
override double Predict (int user_id, int item_id)
 Predict rating or score for a given user-item combination.
virtual void RemoveItem (int item_id)
virtual void RemoveRating (int user_id, int item_id)
virtual void RemoveUser (int user_id)
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.
virtual void UpdateRating (int user_id, int item_id, double rating)

Protected Member Functions

virtual void AddItem (int item_id)
virtual void AddUser (int user_id)
void Train (IList< int > entity_ids, int max_entity_id)
 Train the recommender according to the given entity type.

Protected Attributes

IList< double > entity_averages = new List<double>()
 The average rating for each entity.
double global_average = 0
 The global average rating (default prediction if there is no data about an entity).
double max_rating
 The max rating value.
double min_rating
 The min rating value.
IRatings ratings
 rating data

Properties

int MaxItemID [get, set]
 Maximum item ID.
virtual double MaxRating [get, set]
 The max rating value.
int MaxUserID [get, set]
 Maximum user ID.
virtual double MinRating [get, set]
 The min rating value.
virtual IRatings Ratings [get, set]
 The rating data.
double this [int index] [get]
 return the average rating for a given entity
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

Detailed Description

Uses the average rating value of a user for predictions.

This recommender does NOT support incremental updates.


Member Function Documentation

override bool CanPredict ( int  user_id,
int  item_id 
) [virtual]

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

Reimplemented from RatingPredictor.

Object Clone (  )  [inherited]

create a shallow copy of the object

override void LoadModel ( string  filename  )  [virtual, inherited]

Get the model parameters from a file.

Parameters:
filename the name of the file to read from

Implements RatingPredictor.

override double Predict ( int  user_id,
int  item_id 
) [virtual]

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

Implements RatingPredictor.

override void SaveModel ( string  filename  )  [virtual, inherited]

Save the model parameters to a file.

Parameters:
filename the name of the file to write to

Implements RatingPredictor.

override 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.

Implements IRecommender.

Reimplemented in BiasedMatrixFactorization, FactorWiseMatrixFactorization, ItemAttributeKNN, ItemKNNCosine, ItemKNNPearson, MatrixFactorization, UserAttributeKNN, UserItemBaseline, UserKNNCosine, and UserKNNPearson.

void Train ( IList< int >  entity_ids,
int  max_entity_id 
) [protected, inherited]

Train the recommender according to the given entity type.

Parameters:
entity_ids list of the relevant entity IDs in the training data
max_entity_id the maximum entity ID

Member Data Documentation

IList<double> entity_averages = new List<double>() [protected, inherited]

The average rating for each entity.

double global_average = 0 [protected, inherited]

The global average rating (default prediction if there is no data about an entity).

double max_rating [protected, inherited]

The max rating value.

double min_rating [protected, inherited]

The min rating value.

IRatings ratings [protected, inherited]

rating data


Property Documentation

int MaxItemID [get, set, inherited]

Maximum item ID.

virtual double MaxRating [get, set, inherited]

The max rating value.

Implements IRatingPredictor.

int MaxUserID [get, set, inherited]

Maximum user ID.

virtual double MinRating [get, set, inherited]

The min rating value.

Implements IRatingPredictor.

virtual IRatings Ratings [get, set, inherited]

The rating data.

Reimplemented in ItemKNN, and UserKNN.

double this[int index] [get, inherited]

return the average rating for a given entity

Parameters:
index the entity index
bool UpdateItems [get, set, inherited]

true if items shall be updated when doing incremental updates

Default is true. Set to false if you do not want any updates to the item model parameters when doing incremental updates.

bool UpdateUsers [get, set, inherited]

true if users shall be updated when doing incremental updates

Default is true. Set to false if you do not want any updates to the user model parameters when doing incremental updates.


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