MyMediaLite  3.09
Public Member Functions | Public Attributes | Properties
Ensemble Class Reference

Abtract class for combining several prediction methods. More...

Inheritance diagram for Ensemble:
IRecommender WeightedEnsemble

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
abstract void LoadModel (string file)
 Get the model parameters from a file.
abstract float Predict (int user_id, int item_id)
 Predict rating or score for a given user-item combination.
abstract 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.
abstract void SaveModel (string file)
 Save the model parameters to a file.
string ToString ()
 Return a string representation of the recommender.
virtual void Train ()
 Learn the model parameters of the recommender from the training data.

Public Attributes

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

Properties

float MaxRating [get, set]
 The max rating value.
float MinRating [get, set]
 The min rating value.

Detailed Description

Abtract class for combining several prediction methods.


Member Function Documentation

virtual bool CanPredict ( int  user_id,
int  item_id 
) [inline, virtual]

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]

create a shallow copy of the object

abstract void LoadModel ( string  filename) [pure virtual]

Get the model parameters from a file.

Parameters:
filenamethe name of the file to read from

Implements IRecommender.

Implemented in WeightedEnsemble.

abstract float Predict ( int  user_id,
int  item_id 
) [pure 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 IRecommender.

Implemented in WeightedEnsemble.

abstract IList<Tuple<int, float> > Recommend ( int  user_id,
int  n = 20,
ICollection< int >  ignore_items = null,
ICollection< int >  candidate_items = null 
) [pure 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 IRecommender.

Implemented in WeightedEnsemble.

abstract void SaveModel ( string  filename) [pure virtual]

Save the model parameters to a file.

Parameters:
filenamethe name of the file to write to

Implements IRecommender.

Implemented in WeightedEnsemble.

string ToString ( ) [inherited]

Member Data Documentation

IList<IRecommender> recommenders = new List<IRecommender>()

list of recommenders


Property Documentation

float MaxRating [get, set]

The max rating value.

The max rating value

float MinRating [get, set]

The min rating value.

The min rating value


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