prea.recommender.baseline
Class ItemAverage

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

public class ItemAverage
extends BaselineRecommender

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

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

Field Summary
 SparseVector itemRateAverage
          Average of ratings for each item.
 
Fields inherited from class prea.recommender.baseline.BaselineRecommender
itemCount, maxValue, minValue, rateMatrix, userCount
 
Constructor Summary
ItemAverage(int uc, int ic, double max, double min, SparseVector ira)
          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

itemRateAverage

public SparseVector itemRateAverage
Average of ratings for each item.

Constructor Detail

ItemAverage

public ItemAverage(int uc,
                   int ic,
                   double max,
                   double min,
                   SparseVector ira)
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.
ira - The average of ratings for each item.
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.