Combining several predictors with a weighted ensemble. More...
Public Member Functions | |
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 file) |
Get the model parameters from a file. | |
override float | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination. | |
override void | SaveModel (string file) |
Save the model parameters to a file. | |
string | ToString () |
Return a string representation of the recommender. | |
override void | Train () |
Learn the model parameters of the recommender from the training data. | |
Public Attributes | |
List< IRecommender > | recommenders = new List<IRecommender>() |
list of recommenders | |
List< float > | weights = new List<float>() |
List of component weights. | |
Protected Attributes | |
double | weight_sum |
Sum of the component weights. | |
Properties | |
float | MaxRating [get, set] |
The max rating value. | |
float | MinRating [get, set] |
The min rating value. |
Combining several predictors with a weighted ensemble.
This recommender does NOT support incremental updates.
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.
Object Clone | ( | ) | [inline, inherited] |
create a shallow copy of the object
override void LoadModel | ( | string | filename | ) | [inline, virtual] |
Get the model parameters from a file.
filename | the name of the file to read from |
Implements Ensemble.
override float Predict | ( | int | user_id, | |
int | item_id | |||
) | [inline, virtual] |
Predict rating or score for a given user-item combination.
user_id | the user ID | |
item_id | the item ID |
Implements Ensemble.
override void SaveModel | ( | string | filename | ) | [inline, virtual] |
Save the model parameters to a file.
filename | the name of the file to write to |
Implements Ensemble.
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 BPRLinear, BPRMF, ItemAttributeKNN, ItemKNN, ItemRecommender, MultiCoreBPRMF, SoftMarginRankingMF, UserAttributeKNN, UserKNN, WeightedBPRMF, WeightedItemKNN, WeightedUserKNN, WRMF, BiasedMatrixFactorization, CoClustering, Constant, FactorWiseMatrixFactorization, ItemAttributeKNN, ItemKNNCosine, ItemKNNPearson, LatentFeatureLogLinearModel, MatrixFactorization, RatingPredictor, SigmoidSVDPlusPlus, SocialMF, SVDPlusPlus, TimeAwareBaseline, TimeAwareBaselineWithFrequencies, UserAttributeKNN, UserItemBaseline, UserKNNCosine, and UserKNNPearson.
List<IRecommender> recommenders = new List<IRecommender>() [inherited] |
list of recommenders
double weight_sum [protected] |
Sum of the component weights.
List<float> weights = new List<float>() |
List of component weights.
float MaxRating [get, set, inherited] |
The max rating value.
The max rating value
float MinRating [get, set, inherited] |
The min rating value.
The min rating value