MyMediaLite
3.02
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Attribute-aware rating predictor using Naive Bayes. More...
Public Member Functions | |
override void | AddRatings (IRatings ratings) |
Add new ratings and perform incremental training. | |
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 | |
override void | LoadModel (string filename) |
Get the model parameters from a file. | |
NaiveBayes () | |
Default constructor. | |
override float | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination. | |
virtual void | RemoveItem (int item_id) |
Remove an item from the recommender model, and delete all ratings of this item. | |
override void | RemoveRatings (IDataSet ratings) |
Remove existing ratings and perform "incremental" training. | |
virtual void | RemoveUser (int user_id) |
Remove a user from the recommender model, and delete all their ratings. | |
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. | |
override void | UpdateRatings (IRatings ratings) |
Update existing ratings and perform incremental training. | |
Protected Member Functions | |
virtual void | AddItem (int item_id) |
override void | AddUser (int user_id) |
Protected Attributes | |
float | max_rating |
Maximum rating value. | |
float | min_rating |
Minimum rating value. | |
IRatings | ratings |
rating data | |
Properties | |
float | AttributeSmoothing [get, set] |
Smoothing parameter for the attribute (given class/rating) probabilities. | |
float | ClassSmoothing [get, set] |
Smoothing parameter for the class probabilities (rating priors) | |
SparseBooleanMatrix | ItemAttributes [get, set] |
int | MaxItemID [get, set] |
Maximum item ID. | |
virtual float | MaxRating [get, set] |
Maximum rating value. | |
int | MaxUserID [get, set] |
Maximum user ID. | |
virtual float | MinRating [get, set] |
Minimum rating value. | |
int | NumItemAttributes [get, set] |
virtual IRatings | Ratings [get, set] |
The rating data. | |
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 |
Attribute-aware rating predictor using Naive Bayes.
This recommender supports incremental updates.
NaiveBayes | ( | ) | [inline] |
Default constructor.
override void AddRatings | ( | IRatings | ratings | ) | [inline, virtual] |
Add new ratings and perform incremental training.
ratings | the ratings |
Reimplemented from IncrementalRatingPredictor.
virtual bool CanPredict | ( | int | user_id, |
int | item_id | ||
) | [inline, virtual, inherited] |
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, Constant, SlopeOne, GlobalAverage, UserAverage, ItemAverage, and Random.
Object Clone | ( | ) | [inline, inherited] |
create a shallow copy of the object
override void LoadModel | ( | string | filename | ) | [inline] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements IRecommender.
override float Predict | ( | int | user_id, |
int | item_id | ||
) | [inline] |
Predict rating or score for a given user-item combination.
user_id | the user ID |
item_id | the item ID |
Implements IRecommender.
virtual void RemoveItem | ( | int | item_id | ) | [inline, virtual, inherited] |
Remove an item from the recommender model, and delete all ratings of this item.
It is up to the recommender implementor whether there should be model updates after this action, both options are valid.
item_id | the ID of the user to be removed |
Implements IIncrementalRatingPredictor.
Reimplemented in BiasedMatrixFactorization, MatrixFactorization, and ItemAverage.
override void RemoveRatings | ( | IDataSet | ratings | ) | [inline, virtual] |
Remove existing ratings and perform "incremental" training.
ratings | the user and item IDs of the ratings to be removed |
Reimplemented from IncrementalRatingPredictor.
virtual void RemoveUser | ( | int | user_id | ) | [inline, virtual, inherited] |
Remove a user from the recommender model, and delete all their ratings.
It is up to the recommender implementor whether there should be model updates after this action, both options are valid.
user_id | the ID of the user to be removed |
Implements IIncrementalRatingPredictor.
Reimplemented in BiasedMatrixFactorization, MatrixFactorization, and UserAverage.
override void SaveModel | ( | string | filename | ) | [inline] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements IRecommender.
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.
override void UpdateRatings | ( | IRatings | ratings | ) | [inline, virtual] |
Update existing ratings and perform incremental training.
ratings | the ratings |
Reimplemented from IncrementalRatingPredictor.
float max_rating [protected, inherited] |
Maximum rating value.
float min_rating [protected, inherited] |
Minimum rating value.
float AttributeSmoothing [get, set] |
Smoothing parameter for the attribute (given class/rating) probabilities.
float ClassSmoothing [get, set] |
Smoothing parameter for the class probabilities (rating priors)
SparseBooleanMatrix ItemAttributes [get, set] |
the binary item attributes
Implements IItemAttributeAwareRecommender.
int MaxItemID [get, set, inherited] |
Maximum item ID.
virtual float MaxRating [get, set, inherited] |
Maximum rating value.
Implements IRatingPredictor.
int MaxUserID [get, set, inherited] |
Maximum user ID.
virtual float MinRating [get, set, inherited] |
Minimum rating value.
Implements IRatingPredictor.
int NumItemAttributes [get, set] |
an integer stating the number of attributes
Implements IItemAttributeAwareRecommender.
The rating data.
Implements IRatingPredictor.
Reimplemented in KNN, FactorWiseMatrixFactorization, TimeAwareRatingPredictor, ItemKNN, and UserKNN.
bool UpdateItems [get, set, inherited] |
true if items shall be updated when doing incremental updates
Default should true. Set to false if you do not want any updates to the item model parameters when doing incremental updates.
Implements IIncrementalRatingPredictor.
bool UpdateUsers [get, set, inherited] |
true if users shall be updated when doing incremental updates
Default should be true. Set to false if you do not want any updates to the user model parameters when doing incremental updates.
Implements IIncrementalRatingPredictor.