MyMediaLite  3.04
Public Member Functions | Properties
ITimeAwareRatingPredictor Interface Reference

Interface for time-aware rating predictors. More...

Inheritance diagram for ITimeAwareRatingPredictor:
IRatingPredictor IRecommender TimeAwareRatingPredictor TimeAwareBaseline TimeAwareBaselineWithFrequencies

List of all members.

Public Member Functions

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.
void LoadModel (string filename)
 Get the model parameters from a file.
float Predict (int user_id, int item_id, DateTime time)
 predict rating at a certain point in time
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.
void SaveModel (string filename)
 Save the model parameters to a file.
string ToString ()
 Return a string representation of the recommender.
void Train ()
 Learn the model parameters of the recommender from the training data.

Properties

float MaxRating [get, set]
 Gets or sets the maximum rating.
float MinRating [get, set]
 Gets or sets the minimum rating.
IRatings Ratings [get, set]
 the ratings to learn from
ITimedRatings TimedRatings [get, set]
 training data that also contains the time information

Detailed Description

Interface for time-aware rating predictors.

Time-aware rating predictors use the information contained in the dates/times of the ratings to build more accurate models.

They may or may not use time information at prediction (as opposed to training) time.


Member Function Documentation

bool CanPredict ( int  user_id,
int  item_id 
) [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

Implemented in Ensemble, BiPolarSlopeOne, Recommender, SlopeOne, Constant, GlobalAverage, UserAverage, ItemAverage, and Random.

void LoadModel ( string  filename) [inherited]
float Predict ( int  user_id,
int  item_id,
DateTime  time 
)

predict rating at a certain point in time

Parameters:
user_idthe user ID
item_idthe item ID
timethe time of the rating event

Implemented in TimeAwareBaseline, TimeAwareBaselineWithFrequencies, and TimeAwareRatingPredictor.

float Predict ( int  user_id,
int  item_id 
) [inherited]
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.

void SaveModel ( string  filename) [inherited]
string ToString ( ) [inherited]

Property Documentation

float MaxRating [get, set, inherited]

Gets or sets the maximum rating.

The maximally possible rating

Implemented in RatingPredictor.

float MinRating [get, set, inherited]

Gets or sets the minimum rating.

The minimally possible rating

Implemented in RatingPredictor.

IRatings Ratings [get, set, inherited]

the ratings to learn from

Implemented in KNN, FactorWiseMatrixFactorization, TimeAwareRatingPredictor, RatingPredictor, ItemKNN, and UserKNN.

training data that also contains the time information

Implemented in TimeAwareRatingPredictor.


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