MyMediaLite  3.08
Public Member Functions | Public Attributes | Protected Attributes | Properties
WeightedEnsemble Class Reference

Combining several predictors with a weighted ensemble. More...

Inheritance diagram for WeightedEnsemble:
Ensemble IRecommender

List of all members.

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 IList< Tuple< int,
float > > 
Recommend (int user_id, int n=20, ICollection< int > ignore_items=null, ICollection< int > candidate_items=null)
 Recommend items for a given user.
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

IList< IRecommenderrecommenders = new List<IRecommender>()
 list of recommenders
IList< 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.

Detailed Description

Combining several predictors with a weighted ensemble.

This recommender does NOT support incremental updates.


Member Function Documentation

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.

Parameters:
user_idthe user ID
item_idthe item ID
Returns:
true if a useful prediction can be made, false otherwise

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.

Parameters:
filenamethe 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.

Parameters:
user_idthe user ID
item_idthe item ID
Returns:
the predicted score/rating for the given user-item combination

Implements Ensemble.

override IList<Tuple<int, float> > Recommend ( int  user_id,
int  n = 20,
ICollection< int >  ignore_items = null,
ICollection< int >  candidate_items = null 
) [inline, virtual]

Recommend items for a given user.

Parameters:
user_idthe user ID
nthe number of items to recommend, -1 for as many as possible
ignore_itemscollection if items that should not be returned; if null, use empty collection
candidate_itemsthe candidate items to choose from; if null, use all items
Returns:
a sorted list of (item_id, score) tuples

Implements Ensemble.

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

Save the model parameters to a file.

Parameters:
filenamethe name of the file to write to

Implements Ensemble.

string ToString ( ) [inherited]

Member Data Documentation

IList<IRecommender> recommenders = new List<IRecommender>() [inherited]

list of recommenders

double weight_sum [protected]

Sum of the component weights.

IList<float> weights = new List<float>()

List of component weights.


Property Documentation

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


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