MyMediaLite
3.11
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Uses externally computed predictions More...
Public Member Functions | |
override 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 More... | |
Object | Clone () |
create a shallow copy of the object More... | |
ExternalItemRecommender () | |
Default constructor More... | |
override void | LoadModel (string filename) |
Get the model parameters from a file More... | |
override float | Predict (int user_id, int item_id) |
Predict rating or score for a given user-item combination More... | |
IList< Tuple< int, float > > | Recommend (int user_id, int n=-1, ICollection< int > ignore_items=null, ICollection< int > candidate_items=null) |
Recommend items for a given user More... | |
virtual System.Collections.Generic.IList< Tuple< int, float > > | Recommend (int user_id, int n=-1, System.Collections.Generic.ICollection< int > ignore_items=null, System.Collections.Generic.ICollection< int > candidate_items=null) |
override void | SaveModel (string filename) |
Save the model parameters to a file More... | |
override string | ToString () |
Return a string representation of the recommender More... | |
override void | Train () |
Learn the model parameters of the recommender from the training data More... | |
Properties | |
virtual IPosOnlyFeedback | Feedback [get, set] |
the feedback data to be used for training More... | |
IMapping | ItemMapping [get, set] |
int | MaxItemID [get, set] |
Maximum item ID More... | |
int | MaxUserID [get, set] |
Maximum user ID More... | |
string | PredictionFile [get, set] |
the file with the stored ratings More... | |
IMapping | UserMapping [get, set] |
Uses externally computed predictions
This recommender is for loading predictions made by external (non-MyMediaLite) recommenders, so that we can use MyMediaLite's evaluation framework to evaluate their accuracy.
This recommender does NOT support incremental updates.
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inline |
Default constructor
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inlinevirtual |
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 |
Reimplemented from Recommender.
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inlineinherited |
create a shallow copy of the object
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inlinevirtual |
Get the model parameters from a file
filename | the name of the file to read from |
Reimplemented from Recommender.
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inlinevirtual |
Predict rating or score for a given user-item combination
user_id | the user ID |
item_id | the item ID |
Implements Recommender.
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inherited |
Recommend items for a given user
user_id | the user ID |
n | the number of items to recommend, -1 for as many as possible |
ignore_items | collection if items that should not be returned; if null, use empty collection |
candidate_items | the candidate items to choose from; if null, use all items |
Implemented in WeightedEnsemble, and Ensemble.
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inlinevirtual |
Save the model parameters to a file
filename | the name of the file to write to |
Reimplemented from Recommender.
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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.
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inlinevirtual |
Learn the model parameters of the recommender from the training data
Implements Recommender.
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getsetinherited |
the feedback data to be used for training
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getsetinherited |
Maximum item ID
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getsetinherited |
Maximum user ID
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getset |
the file with the stored ratings