Abstract class for time-aware rating predictors. More...
Public Member Functions | |
virtual 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 | |
virtual void | LoadModel (string file) |
Get the model parameters from a file. | |
abstract double | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination. | |
abstract double | Predict (int user_id, int item_id, DateTime time) |
predict rating at a certain point in time | |
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. | |
Protected Attributes | |
double | max_rating |
Maximum rating value. | |
double | min_rating |
Minimum rating value. | |
IRatings | ratings |
rating data | |
ITimedRatings | timed_ratings |
rating data, including time information | |
Properties | |
int | MaxItemID [get, set] |
Maximum item ID. | |
virtual double | MaxRating [get, set] |
Maximum rating value. | |
int | MaxUserID [get, set] |
Maximum user ID. | |
virtual double | MinRating [get, set] |
Minimum rating value. | |
override IRatings | Ratings [get, set] |
The rating data. | |
virtual ITimedRatings | TimedRatings [get, set] |
the rating data, including time information | |
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 |
Abstract class for time-aware rating predictors.
ArgumentException | Is thrown when an argument passed to a method is invalid. |
virtual bool CanPredict | ( | int | user_id, | |
int | item_id | |||
) | [inline, virtual, inherited] |
Check whether a useful prediction can be made for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Implements IRecommender.
Reimplemented in BiPolarSlopeOne, GlobalAverage, ItemAverage, SlopeOne, and UserAverage.
Object Clone | ( | ) | [inline, inherited] |
create a shallow copy of the object
virtual void LoadModel | ( | string | filename | ) | [inline, virtual, inherited] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements IRecommender.
Reimplemented in BiasedMatrixFactorization, BiPolarSlopeOne, EntityAverage, FactorWiseMatrixFactorization, GlobalAverage, ItemKNN, KNN, MatrixFactorization, SlopeOne, and UserItemBaseline.
abstract double Predict | ( | int | user_id, | |
int | item_id | |||
) | [pure virtual, inherited] |
Predict rating or score for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Implements IRecommender.
Implemented in BiasedMatrixFactorization, BiPolarSlopeOne, FactorWiseMatrixFactorization, GlobalAverage, ItemAverage, ItemKNN, MatrixFactorization, SlopeOne, TimeAwareBaseline, UserAverage, UserItemBaseline, and UserKNN.
abstract double Predict | ( | int | user_id, | |
int | item_id, | |||
DateTime | time | |||
) | [pure virtual] |
predict rating at a certain point in time
user_id | the user ID | |
item_id | the item ID | |
time | the time of the rating event |
Implements ITimeAwareRatingPredictor.
Implemented in TimeAwareBaseline, and TimeAwareBaselineWithFrequencies.
virtual void SaveModel | ( | string | filename | ) | [inline, virtual, inherited] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements IRecommender.
Reimplemented in BiasedMatrixFactorization, BiPolarSlopeOne, EntityAverage, FactorWiseMatrixFactorization, GlobalAverage, KNN, MatrixFactorization, SlopeOne, and UserItemBaseline.
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 BiasedMatrixFactorization, FactorWiseMatrixFactorization, ItemAttributeKNN, ItemKNNCosine, ItemKNNPearson, MatrixFactorization, TimeAwareBaseline, TimeAwareBaselineWithFrequencies, UserAttributeKNN, UserItemBaseline, UserKNNCosine, and UserKNNPearson.
double max_rating [protected, inherited] |
Maximum rating value.
double min_rating [protected, inherited] |
Minimum rating value.
ITimedRatings timed_ratings [protected] |
rating data, including time information
int MaxItemID [get, set, inherited] |
Maximum item ID.
virtual double MaxRating [get, set, inherited] |
Maximum rating value.
Implements IRatingPredictor.
int MaxUserID [get, set, inherited] |
Maximum user ID.
virtual double MinRating [get, set, inherited] |
Minimum rating value.
Implements IRatingPredictor.
The rating data.
Reimplemented from RatingPredictor.
virtual ITimedRatings TimedRatings [get, set] |
the rating data, including time information
Implements ITimeAwareRatingPredictor.
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.