MyMediaLite  3.10
Public Member Functions | Protected Attributes | Properties | List of all members
RatingPredictor Class Reference

Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction) More...

Inheritance diagram for RatingPredictor:
Recommender IRatingPredictor IRecommender IRecommender BiPolarSlopeOne CoClustering ExternalRatingPredictor FactorWiseMatrixFactorization IncrementalRatingPredictor LatentFeatureLogLinearModel SlopeOne TimeAwareRatingPredictor

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
virtual 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
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
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)
virtual void SaveModel (string file)
 Save the model parameters to a file
override string ToString ()
 Return a string representation of the recommender
abstract void Train ()
 Learn the model parameters of the recommender from the training data

Protected Attributes

float max_rating
 Maximum rating value
float min_rating
 Minimum rating value
IRatings ratings
 rating data

Properties

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
virtual IRatings Ratings [get, set]
 The rating data

Detailed Description

Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction)

Member Function Documentation

virtual bool CanPredict ( int  user_id,
int  item_id 
)
inlinevirtualinherited

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.

Reimplemented in ExternalItemRecommender, ExternalRatingPredictor, BiPolarSlopeOne, SlopeOne, Constant, GlobalAverage, UserAverage, ItemAverage, and Random.

Object Clone ( )
inlineinherited

create a shallow copy of the object

virtual void LoadModel ( string  filename)
inlinevirtualinherited
abstract float Predict ( int  user_id,
int  item_id 
)
pure virtualinherited
IList<Tuple<int, float> > Recommend ( int  user_id,
int  n = -1,
ICollection< int >  ignore_items = null,
ICollection< int >  candidate_items = null 
)
inherited

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

Implemented in WeightedEnsemble, and Ensemble.

virtual void SaveModel ( string  filename)
inlinevirtualinherited
override string ToString ( )
inlineinherited
abstract void Train ( )
pure virtualinherited

Member Data Documentation

float max_rating
protected

Maximum rating value

float min_rating
protected

Minimum rating value

IRatings ratings
protected

rating data

Property Documentation

int MaxItemID
getsetinherited

Maximum item ID

virtual float MaxRating
getset

Maximum rating value

int MaxUserID
getsetinherited

Maximum user ID

virtual float MinRating
getset

Minimum rating value

virtual IRatings Ratings
getset

The rating data


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