Random Class Reference

Random item recommender for use as experimental baseline More...

Inheritance diagram for Random:

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 More...
Object	Clone ()
	create a shallow copy of the object 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...
int	MaxItemID [get, set]
	Maximum item ID More...
int	MaxUserID [get, set]
	Maximum user ID More...

Detailed Description

Random item recommender for use as experimental baseline

It would not be necessary for Random to inherit from ItemRecommender, but it is done nonetheless for convenience.

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_id	the user ID
item_id	the 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

override void LoadModel ( string  filename )

inlinevirtual

Get the model parameters from a file

Parameters

filename

the name of the file to read from

Reimplemented from Recommender.

override float Predict ( int  user_id, int  item_id  )

inlinevirtual

Predict rating or score for a given user-item combination

Parameters

user_id	the user ID
item_id	the item ID

Returns

the predicted score/rating for the given user-item combination

Implements Recommender.

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_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

Returns

a sorted list of (item_id, score) tuples

Implemented in WeightedEnsemble, and Ensemble.

override void SaveModel ( string  filename )

inlinevirtual

Save the model parameters to a file

Parameters

filename

the name of the file to write to

Reimplemented from Recommender.

override string ToString ( )

inlineinherited

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.

override void Train ( )

inlinevirtual

Learn the model parameters of the recommender from the training data

Implements Recommender.

Property Documentation

virtual IPosOnlyFeedback Feedback

getsetinherited

the feedback data to be used for training

int MaxItemID

getsetinherited

Maximum item ID

int MaxUserID

getsetinherited

Maximum user ID

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

• ItemRecommendation/Random.cs