prea.recommender.baseline
Class UserAverage

java.lang.Object
  extended by prea.recommender.baseline.BaselineRecommender
      extended by prea.recommender.baseline.UserAverage
All Implemented Interfaces:
Recommender

public class UserAverage
extends BaselineRecommender

The class implementing a baseline, predicting by the average of target user ratings.

Since:
2012. 4. 20
Version:
1.1
Author:
Joonseok Lee

Field Summary
 SparseVector userRateAverage
          Average of ratings for each user.
 
Fields inherited from class prea.recommender.baseline.BaselineRecommender
itemCount, maxValue, minValue, rateMatrix, userCount
 
Constructor Summary
UserAverage(int uc, int ic, double max, double min, SparseVector ura)
          Construct a constant model with the given data.
 
Method Summary
 double predict(int userId, int itemId)
          Predict a rating for the given user and item.
 
Methods inherited from class prea.recommender.baseline.BaselineRecommender
buildModel, evaluate
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

userRateAverage

public SparseVector userRateAverage
Average of ratings for each user.

Constructor Detail

UserAverage

public UserAverage(int uc,
                   int ic,
                   double max,
                   double min,
                   SparseVector ura)
Construct a constant model with the given data.

Parameters:
uc - The number of users in the dataset.
ic - The number of items in the dataset.
max - The maximum rating value in the dataset.
min - The minimum rating value in the dataset.
ura - The average of ratings for each user.
Method Detail

predict

public double predict(int userId,
                      int itemId)
Predict a rating for the given user and item.

Specified by:
predict in class BaselineRecommender
Parameters:
userId - The target user.
itemId - The target item.
Returns:
predicted rating.